Aishwarya Naresh Reganti
Sunnyvale, California, United States
63K followers
500+ connections
About
🚨PLEASE NOTE: I don't check my LinkedIn messages regularly. For speaking, advisory or…
Contributions
Activity
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😎 Nvidia’s latest paper on LLM distillation and pruning has some really interesting insights! It’s well-known that smaller language models are…
😎 Nvidia’s latest paper on LLM distillation and pruning has some really interesting insights! It’s well-known that smaller language models are…
Shared by Aishwarya Naresh Reganti
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💡 Before tackling hallucinations, it's important to know their causes so you can fix the right part. Here's a quick overview: ⛳ Hallucinations can…
💡 Before tackling hallucinations, it's important to know their causes so you can fix the right part. Here's a quick overview: ⛳ Hallucinations can…
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😎 Text-to-SQL is one of the most prevalent enterprise applications of LLMs. If you're in this space, this super comprehensive survey report is a…
😎 Text-to-SQL is one of the most prevalent enterprise applications of LLMs. If you're in this space, this super comprehensive survey report is a…
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Experience
Education
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Carnegie Mellon University
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Relevant Courses:
- Introduction to Computer Systems (15-513)
- Machine learning (10-601)
- Cloud Computing (15-619)
- Interactive Data Science (05-839)
- Introduction to Deep Learning (11-785)
- Large Scale Multimedia Analysis (11-775)
- Deep Reinforcement Learning (10-703)
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Dean’s Academic List
Batch Topper
Dean's Research List -
Volunteer Experience
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Co-Founder
The LevelUp Org
- Present 1 year 10 months
Science and Technology
The LevelUp Org is a self-reliant tech ecosystem and community where members help each other accomplish career goals through 1:1 mentorship programs and a host of other community events
Publications
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A Societal Sentiment Analysis: Predicting the Values and Ethics of Individuals by Analysing Social Media Content
EACL 2017, Valencia, Spain
To find out how users’ social media behaviour and language are related to their ethical practices, the paper investigates applying Schwartz’ psycholinguistic model of societal sentiment to social media text.
The analysis is based on corpora collected from user essays as well as social media
(Facebook and Twitter). Several experiments were carried out on the corpora to classify the ethical values of users, incorporating Linguistic Inquiry Word Count analysis, n-grams, topic models…To find out how users’ social media behaviour and language are related to their ethical practices, the paper investigates applying Schwartz’ psycholinguistic model of societal sentiment to social media text.
The analysis is based on corpora collected from user essays as well as social media
(Facebook and Twitter). Several experiments were carried out on the corpora to classify the ethical values of users, incorporating Linguistic Inquiry Word Count analysis, n-grams, topic models, psycholinguistic lexica, speech-acts, and nonlinguistic information, while applying a range of machine learners (Support Vector Machines, Logistic Regression, and Random Forests) to identify the best linguistic and non-linguistic features for automatic classification of values and ethics. -
Aggression-Annotated Corpus of Hindi-English Code Mixed Data
LREC-2018, Miyazaki,Japan
As the interaction over the web has increased, incidents of aggression and related events like trolling, cyberbullying, flaming, hate speech, etc. too have increased manifold across the globe. While most of these behaviours like bullying or hate speech have predated the Internet, the reach and extent of the Internet has given these an unprecedented power and influence to affect the lives of billions of
people. So it is of utmost significance and importance that some preventive measures be…As the interaction over the web has increased, incidents of aggression and related events like trolling, cyberbullying, flaming, hate speech, etc. too have increased manifold across the globe. While most of these behaviours like bullying or hate speech have predated the Internet, the reach and extent of the Internet has given these an unprecedented power and influence to affect the lives of billions of
people. So it is of utmost significance and importance that some preventive measures be taken to provide safeguard to the people using the web such that the web remains a viable medium of communication and connection, in general. In this paper, we discuss the development of an aggression tagset and an annotated corpus of Hindi-English code-mixed data from two of the most popular social
networking / social media platforms in India – Twitter and Facebook. The corpus is annotated using a hierarchical tagset of 3 top-level tags and 10 level 2 tags. The final dataset contains approximately 18k tweets and 21k facebook comments and is being released for further research in the field -
Mining Human Psycholinguistic Behaviour from Social Media
Information System Frontiers (Springer)-2017
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Modeling Satire in English Text for Automatic Detection - Conference proceedings at
ICDM-Sentire 2016, Barcelona, Spain
According to the Merriam-Webster dictionary, satire is a trenchant wit, irony, or sarcasm used to expose and discredit vice or folly. Though it is an important language aspect used in everyday communication, the study of satire detection in natural text is often ignored. In this paper, we identify key value components and features for automatic satire detection. Our experiments have been carried out on three datasets, namely, tweets, product reviews and newswire articles. We examine the impact…
According to the Merriam-Webster dictionary, satire is a trenchant wit, irony, or sarcasm used to expose and discredit vice or folly. Though it is an important language aspect used in everyday communication, the study of satire detection in natural text is often ignored. In this paper, we identify key value components and features for automatic satire detection. Our experiments have been carried out on three datasets, namely, tweets, product reviews and newswire articles. We examine the impact of a number of state-of-the-art features as well as new generalized textual features. By using these features, we outperform the state of the art by a significant 6% margin.
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Revealing Psycholinguistic Dimensions of Communities in Social Networks
IEEE Intelligent Systems-2018
A community in social networks is generally assumed to be composed of a group of individuals with similar characteristics. Although there has been a plethora of work on understanding network topologies (edge density, clustering coefficient, etc.) within a community, the semantic interpretation of a community has hardly been studied. The present paper aims at understanding whether individuals in a community possess similar Personalities, Values and Ethical backgrounds. To this end, we collect…
A community in social networks is generally assumed to be composed of a group of individuals with similar characteristics. Although there has been a plethora of work on understanding network topologies (edge density, clustering coefficient, etc.) within a community, the semantic interpretation of a community has hardly been studied. The present paper aims at understanding whether individuals in a community possess similar Personalities, Values and Ethical backgrounds. To this end, we collect datasets from various social media platforms (including Facebook, Twitter), which contain Values and Ethics of users. Then we design a three-fold experimental setup. First, we propose automatic models to determine Personality and Values (Values and Ethics) of individuals by analyzing their language usage and behaviour in social media. Secondly, various experiments are performed to understand the characteristics or …
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Semantic Interpretation of Social Network Communities
AAAI 2017 , San Francisco, USA.
A community in a social network is considered to be a group of nodes densely connected internally and sparsely connected externally. Although previous work intensely studied network topology within a community, its semantic interpretation is hardly understood. In this paper, we attempt to understand whether individuals in a community possess similar Personalities, Values and Ethical background. Finally, we show that Personality and Values models could be used as features to discover more…
A community in a social network is considered to be a group of nodes densely connected internally and sparsely connected externally. Although previous work intensely studied network topology within a community, its semantic interpretation is hardly understood. In this paper, we attempt to understand whether individuals in a community possess similar Personalities, Values and Ethical background. Finally, we show that Personality and Values models could be used as features to discover more accurate community structure compared to the one obtained from only network information.
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Socio-Ethnic Ingredients of Social Network Communities
CSCW 2017, Portland, Oregon, USA
Description
In network science, a community is considered to be a group of nodes densely connected internally and sparsely connected externally. Detecting and analyzing communities from social networks has attracted immense attention over the last decade. However, the semantic interpretation of a community is hardly studied. In this paper, we attempt to understand {em whether individuals in a community possess similar personalities, values and ethical background}. To this end, we collect…
Description
In network science, a community is considered to be a group of nodes densely connected internally and sparsely connected externally. Detecting and analyzing communities from social networks has attracted immense attention over the last decade. However, the semantic interpretation of a community is hardly studied. In this paper, we attempt to understand {em whether individuals in a community possess similar personalities, values and ethical background}. To this end, we collect Twitter values corpus, extract the network communities and propose automatic models to determine personality, values, considered as ethnicity of individuals. Various experiments are performed to understand the characteristics or blend of characteristics of individuals within a community. -
Understanding Psycho-Sociological Vulnerability of ISIS Patronizers in Twitter.
ASONAM-2017,Sydney, Australia
Projects
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Capstone: Designing Code-Mixed Goal Oriented Conversation Systems for Hindi Movies (Advisor: Prof. Alan Black)
- Present
Code mixing/switching (for the scope of this project, we use the two terms interchangeably) is the phenomenon of mixing two or more languages in speech/text communication. Over the past few years, code mixing has become the default code of communication in geographical regions like India where there is a high percentage of multilingual individuals. Although state-of-the-art conversational systems and language models produce good quality monolingual utterances, they struggle with code-mixed data…
Code mixing/switching (for the scope of this project, we use the two terms interchangeably) is the phenomenon of mixing two or more languages in speech/text communication. Over the past few years, code mixing has become the default code of communication in geographical regions like India where there is a high percentage of multilingual individuals. Although state-of-the-art conversational systems and language models produce good quality monolingual utterances, they struggle with code-mixed data generation because of lack of data compounded by the increased confusability about the language structure and switching points. In this work, we aim to focus on building a goal-oriented Hinglish (Hindi and English code-mixed) dialogue system trained on data curated from code-mixed conversations about Hindi movies. We also aim to make the system more socially engaging and context-aware as compared to mainstream conversational agents. The contributions of our work include: (i) developing a new corpus for code-mixed movie conversations, (ii) building language models that can generate grammatically correct code-mixed utterances and finally, (iii) compiling an end-to-end goal-oriented dialogue system that can have engaging conversations about Hindi movies with prospective users.
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Understanding Sociological Vulnerability of Partonisers on Twitter
Terrorist Organisations make extensive use of online social media platforms to promulgate their ideologies and evoke many individuals, particularly young people, to support the organization, and take part in their war. The sociological backgrounds of an individual play a very crucial role in determining his/her vulnerability of being lured into joining the organisation and indulge in terrorist activities. In this work, we analyse several sociological aspects (Values & Ethics, Personality…
Terrorist Organisations make extensive use of online social media platforms to promulgate their ideologies and evoke many individuals, particularly young people, to support the organization, and take part in their war. The sociological backgrounds of an individual play a very crucial role in determining his/her vulnerability of being lured into joining the organisation and indulge in terrorist activities. In this work, we analyse several sociological aspects (Values & Ethics, Personality, Optimism /Pessimism, Age & Gender, Veridicality, Life Satisfaction, Mental Health, Implication Analysis) to understand the Sociological Vulnerability of individuals over the social media platform ’Twitter’ using their links with Terrorist Representatives and their Social media Posts. The sociological patterns thus obtained, can be used to determine the vulnerability of any given twitter user by using these patterns as metrics to gauge the the possibility of recruitment into the organisation
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Figurative Language Analysis
Figurative language is language that uses words or expressions with a meaning that is different from the literal interpretation. Figurative language is used with a meaning that is different from the basic meaning and that expresses an idea in an interesting way by using language that usually describes something else. Therefore, one of the greatest challenges in computational linguistics is figurative language processing, since the words or expressions used possess a meaning that is different…
Figurative language is language that uses words or expressions with a meaning that is different from the literal interpretation. Figurative language is used with a meaning that is different from the basic meaning and that expresses an idea in an interesting way by using language that usually describes something else. Therefore, one of the greatest challenges in computational linguistics is figurative language processing, since the words or expressions used possess a meaning that is different from the literal interpretation. In my summer internship at NTU Singapore, I worked on analysis of various elements of figurative language. My team also developed an automatic satire detection system, we published a research paper on the works carried out in ICDM-Sentire-2016
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Semantic Interpretation of Social Network Communities
In network science, a community is considered to be a group of nodes densely connected internally and sparsely connected externally. However, the semantic interpretation of a community is hardly studied. In this project, my team attempts to understand whether individuals in a community possess similar Personalities, Values and Ethical background. Finally, we show that Personality and Values models could be used as features to discover more accurate community structure compared to the one…
In network science, a community is considered to be a group of nodes densely connected internally and sparsely connected externally. However, the semantic interpretation of a community is hardly studied. In this project, my team attempts to understand whether individuals in a community possess similar Personalities, Values and Ethical background. Finally, we show that Personality and Values models could be used as features to discover more accurate community structure compared to the one obtained from only network information.
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Values/Personality Community World Map
To understand how someone’s personality and intrinsic values change with geolocation and city we intend to perform several experiments, the final outcome of which will be a map to represent geo-specific values.In order to create the World map, we intend to collect data from 40 most popular cities around the world. We will also be collecting the network structure of atleast 2000 users from each city and determine the Values and Personality and checking community Variations all over the world…
To understand how someone’s personality and intrinsic values change with geolocation and city we intend to perform several experiments, the final outcome of which will be a map to represent geo-specific values.In order to create the World map, we intend to collect data from 40 most popular cities around the world. We will also be collecting the network structure of atleast 2000 users from each city and determine the Values and Personality and checking community Variations all over the world. This values/ethics map would provide an overview of the kind of values & Personalities possessed by people from different regions and community structure.
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Personality Detection from Social Network Profiles
According to statistics Facebook is the 2nd most popular and Twitter is the 10th most popular website now! Probably the meaning space of social-status and Facebook/Twitter status is coming closer day by day. There could be a perpetual debate on whether digital representations of us on Facebook/Twitter can capture much about human social relations, but the increasing popularity of these sites and data made urgency to develop technology to manage this information more intelligently than ever…
According to statistics Facebook is the 2nd most popular and Twitter is the 10th most popular website now! Probably the meaning space of social-status and Facebook/Twitter status is coming closer day by day. There could be a perpetual debate on whether digital representations of us on Facebook/Twitter can capture much about human social relations, but the increasing popularity of these sites and data made urgency to develop technology to manage this information more intelligently than ever. With that necessity in mind the goal of my present research is to assess personality(Openness (O),Conscientiousness (C),Extraversion (E), Agreeableness (A), Neuroticism (N)called Big Five Model)of any user from his/her Facebook/Twitter interactions.
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Sentiment Analysis of Code-Mixed text
Sentiment Analysis seeks to identify the opinions and viewpoints communicated in a given piece of data which is generally in the form of text. In the recent years, there have been many attempts to classify texts from various sources based on their polarity. However, a major challenge in analyzing textual data is Code-Mixing. Especially, in a multilingual country like India where about 22 official languages exist, Code-Mixing is very prominent. For example, many native languages are Code-Mixed…
Sentiment Analysis seeks to identify the opinions and viewpoints communicated in a given piece of data which is generally in the form of text. In the recent years, there have been many attempts to classify texts from various sources based on their polarity. However, a major challenge in analyzing textual data is Code-Mixing. Especially, in a multilingual country like India where about 22 official languages exist, Code-Mixing is very prominent. For example, many native languages are Code-Mixed in English script. In this project, my team attempts to provide a sentiment analysis of Telugu, Tamil and Hindi social media textual content obtained from various kind of social media sources like Twitter, Facebook e.t.c. The model will classify a given text into positive, negative and neutral.
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Web Portal for University Hostel
Developed a Hostel portal for the University to facilitate hostelers using web2py framework and SQLite database. User Interface was developed using Java-Script, HTML and bootstrap.
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Quad Control Robotic Arm for Assistance of Physically Challenged(Android-Based)
Developed a prototype Robotic Arm for assisting aged and Physically Challenged people. The Arm uses Wi-Fi and Bluetooth as communication networks and works on four control mechanisms i.e., Remote, Smart Phone Tilt, Voice and Hand gesture recognition. User Interface is provided by self developed Android Application
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Joke On Point! - Neural Joke Generation using Pointer-Generator Networks
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Neural networks have been widely applied to a variety of natural language tasks. However, their application to creative language generation has been limited so far. While current state-of-the-art neural models produce unprecedented quality of jokes, they are still far from human quality. We identify two major drawbacks in existing joke generation models namely - syntactic correctness and semantic coherence and take small steps to better them. We use a pointer-generator network and multi-task…
Neural networks have been widely applied to a variety of natural language tasks. However, their application to creative language generation has been limited so far. While current state-of-the-art neural models produce unprecedented quality of jokes, they are still far from human quality. We identify two major drawbacks in existing joke generation models namely - syntactic correctness and semantic coherence and take small steps to better them. We use a pointer-generator network and multi-task learning with the primary objective of predicting a word at the current time-step and secondary objective of predicting the Part-Of-Speech (POS) tag for the next time-step. Our model outperforms the state of the art on the given dataset in the domain of joke generation.
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Multimodal Video Summarization
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State of the art text summarization models work notably well for standard news datasets like CNN/DailyMail. However, they struggle to produce reasonable results with new domains like video transcript summarization. This can be attributed to the drastic shift in sentence and summary structures. Moreover, most summarization systems do not use multimodal attributes which have proved to help produce better output quality in other similar language tasks. In this project, we develop a multimodal…
State of the art text summarization models work notably well for standard news datasets like CNN/DailyMail. However, they struggle to produce reasonable results with new domains like video transcript summarization. This can be attributed to the drastic shift in sentence and summary structures. Moreover, most summarization systems do not use multimodal attributes which have proved to help produce better output quality in other similar language tasks. In this project, we develop a multimodal summarization model using the How2 instructional video dataset using two successive summarization components, an extractor that extracts key summary sentences and an abstractor that paraphrases key sentences coherently. We use RL based policy update method to fine tune these components. Our model obtains a ROUGE-L of 47.3, which is an improvement over other tried pointer-generator based models. Human evaluation shows that our model is able to produce summaries containing key information from the video transcripts using video features
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Semantic Interpretation of Aggression from Code-Mixed Social Media Posts
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In recent years, aggressive posts on social media have grown substantially which has serious implications for all social media users. While many previous research works have looked at aggression detection for monolingual data, there are very few works for code-mixed data. In this paper, we address the challenge of automatically identifying aggression in code-mixed (Hinglish) social media posts. We present a novel hierarchical attention model for aggression classification. The model outperforms…
In recent years, aggressive posts on social media have grown substantially which has serious implications for all social media users. While many previous research works have looked at aggression detection for monolingual data, there are very few works for code-mixed data. In this paper, we address the challenge of automatically identifying aggression in code-mixed (Hinglish) social media posts. We present a novel hierarchical attention model for aggression classification. The model outperforms the state-of-the-art for this task and also helps improve the explainability of classification.
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Home Automation System with user Face Recognition
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Devised a Home Automation System which validates user on the basis of face recognition using MATLAB and Raspberry Pi
Honors & Awards
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ACM-W Travel Grant for AAAI-2017
Association for Computing Machinery- Women in Computing
https://women.acm.org/scholars/acm-w-scholars/aishwarya-naresh-reganti/
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Scholar Badge for Academic Excellence
Delhi Public School, Bangalore South
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Batch Topper
Indian Institute of Information Technology, Sri City
Btech(Hons.) Electronics and Communication Engineering
Languages
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English
Full professional proficiency
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Telugu
Native or bilingual proficiency
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Tamil
Native or bilingual proficiency
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Kannada
Native or bilingual proficiency
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Hindi
Professional working proficiency
More activity by Aishwarya
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😎 Anthropic just shared the system prompts for different Claude models, and there are some really interesting takeaways! ⛳ Opus stands out as the…
😎 Anthropic just shared the system prompts for different Claude models, and there are some really interesting takeaways! ⛳ Opus stands out as the…
Shared by Aishwarya Naresh Reganti
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😅 The pace of RAG research is super impressive, but not all of it is practical for real-world use cases. Many latest research works seek to…
😅 The pace of RAG research is super impressive, but not all of it is practical for real-world use cases. Many latest research works seek to…
Shared by Aishwarya Naresh Reganti
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𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈 𝐰𝐢𝐭𝐡 𝐀𝐦𝐚𝐳𝐨𝐧 𝐁𝐞𝐝𝐫𝐨𝐜𝐤: 𝐚 𝐦𝐮𝐬𝐭 𝐫𝐞𝐚𝐝! I don’t usually recommend specific books on Generative AI…
𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈 𝐰𝐢𝐭𝐡 𝐀𝐦𝐚𝐳𝐨𝐧 𝐁𝐞𝐝𝐫𝐨𝐜𝐤: 𝐚 𝐦𝐮𝐬𝐭 𝐫𝐞𝐚𝐝! I don’t usually recommend specific books on Generative AI…
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