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cs.CL2026
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…
cs.CL2025
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…
cs.CL2024
Towards Compositionality in Concept Learning
Adam Stein, Aaditya Naik, Yinjun Wu +2
Concept-based interpretability methods offer a lens into the internals of foundation models by decomposing their embeddings into high-level concepts. These concept representations…