51 citations · 266 across the 32 of their papers we have counts for
6 papers · 1 filter
Steerable Cultural Preference Optimization of Reward Models
Minsik Oh, Advit Deepak, Sophie Wu +2
It is essential for large language model (LLM) technology to serve many different cultural sub-communities in a manner that is acceptable to each community. However, research on LL…
Single-Agent LLMs Outperform Multi-Agent Systems on Multi-Hop Reasoning Under Equal Thinking Token Budgets
Dat Tran, Douwe Kiela
Recent work reports strong performance from multi-agent LLM systems (MAS), but these gains are often confounded by increased test-time computation. When computation is normalized,…
Reflective Context Learning: Studying the Optimization Primitives of Context Space
Nikita Vassilyev, William Berrios, Ruowang Zhang +3
Generally capable agents must learn from experience in ways that generalize across tasks and environments. The fundamental problems of learning, including credit assignment, overfi…
Document Optimization for Black-Box Retrieval via Reinforcement Learning
Omri Uzan, Ron Polonsky, Douwe Kiela +1
Generative large language models (LLMs) are increasingly used as inference-time components in retrieval pipelines, for tasks such as query rewriting and document reranking. However…
ExtractBench: A Benchmark and Evaluation Methodology for Complex Structured Extraction
Nick Ferguson, Josh Pennington, Narek Beghian +4
Unstructured documents like PDFs contain valuable structured information, but downstream systems require this data in reliable, standardized formats. LLMs are increasingly deployed…
BlitzRank: Principled Zero-shot Ranking Agents with Tournament Graphs
Sheshansh Agrawal, Thien Hang Nguyen, Douwe Kiela
Selecting the top from items via expensive -wise comparisons is central to settings ranging from LLM-based document reranking to crowdsourced evaluation and tournament d…