4 citations · 9 across the 9 of their papers we have counts for
9 papers
Diversity Augmentation of Dynamic User Preference Data for Boosting Personalized Text Summarizers
Parthiv Chatterjee, Shivam Sonawane, Amey Hengle +3
Document summarization enables efficient extraction of user-relevant content but is inherently shaped by individual subjectivity, making it challenging to identify subjective salie…
Can LLMs reason over extended multilingual contexts? Towards long-context evaluation beyond retrieval and haystacks
Amey Hengle, Prasoon Bajpai, Soham Dan +1
Existing multilingual long-context benchmarks, often based on the popular needle-in-a-haystack test, primarily evaluate a model's ability to locate specific information buried with…
CSEval: Towards Automated, Multi-Dimensional, and Reference-Free Counterspeech Evaluation using Auto-Calibrated LLMs
Amey Hengle, Aswini Kumar, Anil Bandhakavi +1
Counterspeech has emerged as a popular and effective strategy for combating online hate speech, sparking growing research interest in automating its generation using language model…
Still Not Quite There! Evaluating Large Language Models for Comorbid Mental Health Diagnosis
Amey Hengle, Atharva Kulkarni, Shantanu Patankar +4
In this study, we introduce ANGST, a novel, first-of-its kind benchmark for depression-anxiety comorbidity classification from social media posts. Unlike contemporary datasets that…
Multilingual Needle in a Haystack: Investigating Long-Context Behavior of Multilingual Large Language Models
Amey Hengle, Prasoon Bajpai, Soham Dan +1
While recent large language models (LLMs) demonstrate remarkable abilities in responding to queries in diverse languages, their ability to handle long multilingual contexts is unex…
Intent-conditioned and Non-toxic Counterspeech Generation using Multi-Task Instruction Tuning with RLAIF
Amey Hengle, Aswini Kumar, Sahajpreet Singh +3
Counterspeech, defined as a response to mitigate online hate speech, is increasingly used as a non-censorial solution. Addressing hate speech effectively involves dispelling the st…
Counting the Bugs in ChatGPT's Wugs: A Multilingual Investigation into the Morphological Capabilities of a Large Language Model
Leonie Weissweiler, Valentin Hofmann, Anjali Kantharuban +10
Large language models (LLMs) have recently reached an impressive level of linguistic capability, prompting comparisons with human language skills. However, there have been relative…
Combining Context-Free and Contextualized Representations for Arabic Sarcasm Detection and Sentiment Identification
Amey Hengle, Atharva Kshirsagar, Shaily Desai +1
Since their inception, transformer-based language models have led to impressive performance gains across multiple natural language processing tasks. For Arabic, the current state-o…
An Attention Ensemble Approach for Efficient Text Classification of Indian Languages
Atharva Kulkarni, Amey Hengle, Rutuja Udyawar
The recent surge of complex attention-based deep learning architectures has led to extraordinary results in various downstream NLP tasks in the English language. However, such rese…