40 citations · 122 across the 24 of their papers we have counts for
24 papers
ToolAlignBench: Investigating Alignment Conflicts in Tool-Calling Enabled LLMs
Aryan Keluskar, Amrita Bhattacharjee, Huan Liu
Safety alignment in LLMs aims to align models with human values, but which values take precedence when they conflict? We investigate this question in the context of tool-calling LL…
When Does Personality Composition Matter for Multi-Agent LLM Teams?
Aryan Keluskar, Amrita Bhattacharjee, Huan Liu
Personality prompting shapes how large language models communicate, yet whether these behavioral shifts affect objective task outcomes remains under-explored. Prior work shows that…
Do LLMs Understand Ambiguity in Text? A Case Study in Open-world Question Answering
Aryan Keluskar, Amrita Bhattacharjee, Huan Liu
Ambiguity in natural language poses significant challenges to Large Language Models (LLMs) used for open-domain question answering. LLMs often struggle with the inherent uncertaint…
From Generation to Judgment: Opportunities and Challenges of LLM-as-a-judge
Dawei Li, Bohan Jiang, Liangjie Huang +10
Assessment and evaluation have long been critical challenges in artificial intelligence (AI) and natural language processing (NLP). Traditional methods, usually matching-based or s…
Defending Against Social Engineering Attacks in the Age of LLMs
Lin Ai, Tharindu Kumarage, Amrita Bhattacharjee +12
The proliferation of Large Language Models (LLMs) poses challenges in detecting and mitigating digital deception, as these models can emulate human conversational patterns and faci…
Extracting Heuristics from Large Language Models for Reward Shaping in Reinforcement Learning
Siddhant Bhambri, Amrita Bhattacharjee, Durgesh Kalwar +3
Reinforcement Learning (RL) suffers from sample inefficiency in sparse reward domains, and the problem is further pronounced in case of stochastic transitions. To improve the sampl…