5 papers
UNSPECIFIC: General Constraint Synthesis for Breaking Copy-and-Paste Shortcut in LLM Instruction Following
Jeet Sharma, Balpreet Kaur, Jeremiah Hong +2
Large language models (LLMs) are increasingly expected to follow long lists of constraints in complex instructions, and synthesizing instructions from a reference document (i.e., b…
Your Mouse and Eyes Secretly Leak Your Preference: LLM Alignment using Implicit Feedback from Users
Haw-Shiuan Chang, Jeffrey Gomez, Mehul Patwari +2
To align a Large Language Model (LLM), most existing methods collect explicit human feedback and train a reward model to predict the human preference based on the response text. Th…
PROMPT2BOX:Improving LLM Weakness Discovery and Specificity Estimation by Uncovering Entailment Structure among Prompts
Neeladri Bhuiya, Shib Sankar Dasgupta, Andrew McCallum +1
To discover the weaknesses of LLMs, researchers often embed prompts into a vector space and cluster them to extract insightful patterns. However, vector embeddings primarily captur…
Truncated Step-Level Sampling with Process Rewards for Retrieval-Augmented Reasoning
Chris Samarinas, Haw-Shiuan Chang, Hamed Zamani
Reinforcement learning has emerged as an effective paradigm for training large language models to interleave reasoning with search engine calls. However, existing approaches face a…
CoKe: Customizable Fine-Grained Story Evaluation via Chain-of-Keyword Rationalization
Brihi Joshi, Sriram Venkatapathy, Mohit Bansal +2
Evaluating creative text such as human-written stories using language models has always been a challenging task -- owing to the subjectivity of multi-annotator ratings. To mimic th…