6 papers
Detecting Safety Violations Across Many Agent Traces
Adam Stein, Davis Brown, Hamed Hassani +2
To identify safety violations, auditors often search over large sets of agent traces. This search is difficult because failures are often rare, complex, and sometimes even adversar…
Instruction Following by Principled Boosting Attention of Large Language Models
Vitoria Guardieiro, Avishree Khare, Adam Stein +1
Large language models' behavior is often shaped by instructions such as system prompts, refusal boundaries, privacy constraints, and tool-use rules that must hold at inference time…
Once Upon an Input: Reasoning via Per-Instance Program Synthesis
Adam Stein, Neelay Velingker, Mayur Naik +1
Large language models (LLMs) excel at zero-shot inference but continue to struggle with complex, multi-step reasoning. Recent methods that augment LLMs with intermediate reasoning…
Towards Style Alignment in Cross-Cultural Translation
Shreya Havaldar, Adam Stein, Eric Wong +1
Successful communication depends on the speaker's intended style (i.e., what the speaker is trying to convey) aligning with the listener's interpreted style (i.e., what the listene…
The Road to Generalizable Neuro-Symbolic Learning Should be Paved with Foundation Models
Adam Stein, Aaditya Naik, Neelay Velingker +2
Neuro-symbolic learning was proposed to address challenges with training neural networks for complex reasoning tasks with the added benefits of interpretability, reliability, and e…
Where's the Bug? Attention Probing for Scalable Fault Localization
Adam Stein, Arthur Wayne, Aaditya Naik +2
Ensuring code correctness remains a challenging problem even as large language models (LLMs) become increasingly capable at code-related tasks. While LLM-based program repair syste…