Papers by Wencheng Ye

1 papers
RISER: Orchestrating Latent Reasoning Skills for Adaptive Activation Steering (2026.findings-acl)

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Challenge: Existing methods for domain-specific reasoning with large language models require updating parameter updates.
Approach: They propose a plug-and-play intervention framework that adaptively steers LLM reasoning in activation space.
Outcome: The proposed framework achieves zero-shot accuracy improvements of 3.4–6.5% over the base model while outperforming chain-of-thought-style reasoning with 2–3 higher token efficiency and robust accuracy gains.

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