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20232026
most citedFactuality of Large Language Models: A Survey

7 citations · 18 across the 13 of their papers we have counts for

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9 papers · 1 filter

cs.CL2025

Llama-3-Nanda-10B-Chat: An Open Generative Large Language Model for Hindi

Monojit Choudhury, Shivam Chauhan, Rocktim Jyoti Das +27

Developing high-quality large language models (LLMs) for moderately resourced languages presents unique challenges in data availability, model adaptation, and evaluation. We introd…

cs.CL2024

MediTOD: An English Dialogue Dataset for Medical History Taking with Comprehensive Annotations

Vishal Vivek Saley, Goonjan Saha, Rocktim Jyoti Das +2

Medical task-oriented dialogue systems can assist doctors by collecting patient medical history, aiding in diagnosis, or guiding treatment selection, thereby reducing doctor burnou…

cs.CL2024

Synergizing In-context Learning with Hints for End-to-end Task-oriented Dialog Systems

Vishal Vivek Saley, Rocktim Jyoti Das, Dinesh Raghu +1

End-to-end Task-Oriented Dialog (TOD) systems typically require extensive training datasets to perform well. In contrast, large language model (LLM) based TOD systems can excel eve…

cs.CL2024

From Multiple-Choice to Extractive QA: A Case Study for English and Arabic

Teresa Lynn, Malik H. Altakrori, Samar Mohamed Magdy +11

The rapid evolution of Natural Language Processing (NLP) has favoured major languages such as English, leaving a significant gap for many others due to limited resources. This is e…

cs.CL2024★ 2 cited

EXAMS-V: A Multi-Discipline Multilingual Multimodal Exam Benchmark for Evaluating Vision Language Models

Rocktim Jyoti Das, Simeon Emilov Hristov, Haonan Li +3

We introduce EXAMS-V, a new challenging multi-discipline multimodal multilingual exam benchmark for evaluating vision language models. It consists of 20,932 multiple-choice questio…

cs.CL2024★ 7 cited

Factuality of Large Language Models: A Survey

Yuxia Wang, Minghan Wang, Muhammad Arslan Manzoor +4

Large language models (LLMs), especially when instruction-tuned for chat, have become part of our daily lives, freeing people from the process of searching, extracting, and integra…

cs.CL2023★ 1 cited

Beyond Size: How Gradients Shape Pruning Decisions in Large Language Models

Rocktim Jyoti Das, Mingjie Sun, Mukul Ranjan +2

Large Language Models (LLMs) with billions of parameters are prime targets for network pruning, which removes some model weights without hurting performance. Prior approaches such…

cs.CL2023

DKAF: KB Arbitration for Learning Task-Oriented Dialog Systems with Dialog-KB Inconsistencies

Vishal Vivek Saley, Rocktim Jyoti Das, Dinesh Raghu +1

Task-oriented dialog (TOD) agents often ground their responses on external knowledge bases (KBs). These KBs can be dynamic and may be updated frequently. Existing approaches for le…

cs.CL2023★ 4 cited

Exploring Distributional Shifts in Large Language Models for Code Analysis

Shushan Arakelyan, Rocktim Jyoti Das, Yi Mao +1

We systematically study how three large language models with code capabilities - CodeT5, Codex, and ChatGPT - generalize to out-of-domain data. We consider two fundamental applicat…