2 citations · 3 across the 12 of their papers we have counts for
7 papers · 1 filter
EduVidQA: Generating and Evaluating Long-form Answers to Student Questions based on Lecture Videos
Sourjyadip Ray, Shubham Sharma, Somak Aditya +1
As digital platforms redefine educational paradigms, ensuring interactivity remains vital for effective learning. This paper explores using Multimodal Large Language Models (MLLMs)…
AURA: Affordance-Understanding and Risk-aware Alignment Technique for Large Language Models
Sayantan Adak, Pratyush Chatterjee, Somnath Banerjee +3
Present day LLMs face the challenge of managing affordance-based safety risks-situations where outputs inadvertently facilitate harmful actions due to overlooked logical implicatio…
REFINE-AF: A Task-Agnostic Framework to Align Language Models via Self-Generated Instructions using Reinforcement Learning from Automated Feedback
Aniruddha Roy, Pretam Ray, Abhilash Nandy +2
Instruction-based Large Language Models (LLMs) have proven effective in numerous few-shot or zero-shot Natural Language Processing (NLP) tasks. However, creating human-annotated in…
ERVQA: A Dataset to Benchmark the Readiness of Large Vision Language Models in Hospital Environments
Sourjyadip Ray, Kushal Gupta, Soumi Kundu +3
The global shortage of healthcare workers has demanded the development of smart healthcare assistants, which can help monitor and alert healthcare workers when necessary. We examin…
MATHSENSEI: A Tool-Augmented Large Language Model for Mathematical Reasoning
Debrup Das, Debopriyo Banerjee, Somak Aditya +1
Tool-augmented Large Language Models (TALMs) are known to enhance the skillset of large language models (LLMs), thereby, leading to their improved reasoning abilities across many t…
TEXT2AFFORD: Probing Object Affordance Prediction abilities of Language Models solely from Text
Sayantan Adak, Daivik Agrawal, Animesh Mukherjee +1
We investigate the knowledge of object affordances in pre-trained language models (LMs) and pre-trained Vision-Language models (VLMs). A growing body of literature shows that PTLMs…
Code Prompting Elicits Conditional Reasoning Abilities in Text+Code LLMs
Haritz Puerto, Martin Tutek, Somak Aditya +2
Reasoning is a fundamental component of language understanding. Recent prompting techniques, such as chain of thought, have consistently improved LLMs' performance on various reaso…