6 papers
Self-Compacting Language Model Agents
Tianjian Li, Jingyu Zhang, William Jurayj +5
Long agent traces composed of chains of thought and tool calls accumulate stale content that anchor subsequent generations, and eventually outgrow the context window. Existing scaf…
Many-Tier Instruction Hierarchy in LLM Agents
Jingyu Zhang, Tianjian Li, William Jurayj +3
Large language model agents receive instructions from many sources-system messages, user prompts, tool outputs, other agents, and more-each carrying different levels of trust and a…
DeonticBench: A Benchmark for Reasoning over Rules
Guangyao Dou, Luis Brena, Akhil Deo +4
Reasoning with complex, context-specific rules remains challenging for large language models (LLMs). In legal and policy settings, this manifests as deontic reasoning: reasoning ab…
Are Finer Citations Always Better? Rethinking Granularity for Attributed Generation
Hexuan Wang, Jingyu Zhang, Benjamin Van Durme +1
Citation granularity - whether to cite individual sentences, paragraphs, or documents - is a critical design choice in attributed generation. While fine-grained citations are often…
RATIONALYST: Mining Implicit Rationales for Process Supervision of Reasoning
Dongwei Jiang, Guoxuan Wang, Yining Lu +5
The reasoning steps generated by LLMs might be incomplete, as they mimic logical leaps common in everyday communication found in their pre-training data: underlying rationales are…
Certified Mitigation of Worst-Case LLM Copyright Infringement
Jingyu Zhang, Jiacan Yu, Marc Marone +2
The exposure of large language models (LLMs) to copyrighted material during pre-training raises concerns about unintentional copyright infringement post deployment. This has driven…