25 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…
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…
Critic-R: Improving Agentic Search using Instruction-tuned Retrievers with Natural Language Introspective Feedback
Md Zarif Ul Alam, Alireza Salemi, Hamed Zamani
Agentic search systems iteratively interact with retrieval models to answer complex queries. Despite substantial progress, optimizing retrievers for agentic search remains challeng…
GrepSeek: Training Search Agents for Direct Corpus Interaction
Alireza Salemi, Chang Zeng, Atharva Nijasure +4
Large Language Model (LLM) search agents have shown strong promise for knowledge-intensive language tasks through multiple rounds of reasoning and information retrieval. Most exist…
Uncertainty Quantification for Retrieval-Augmented Reasoning
Heydar Soudani, Hamed Zamani, Faegheh Hasibi
Retrieval-augmented reasoning (RAR) is a recent evolution of retrieval-augmented generation (RAG) that employs multiple reasoning steps for retrieval and generation. While effectiv…
Learning from Natural Language Feedback for Personalized Question Answering
Alireza Salemi, Hamed Zamani
Personalization is crucial for enhancing both the effectiveness and user satisfaction of language technologies, particularly in information-seeking tasks like question answering. C…