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B. Lim

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#artificial intelligence Preprint Sep 2026

Look Before You Leap: Factual Decoding with Internal Attribution Signals

This work identifies a factual-salient layer span within LLMs whose derived signal is selectively elevated for factual tokens and exhibits anomalous spikes at hallucination-prone steps, and proposes DescaPE, a decoding framework that leverages internal model signals to suppress hallucination-prone trajectories at infer...

Hayeong Ryu, Jungmin Yun, B. Lim et al. · 0 citations
#natural language process... Preprint Aug 2026

ALTSTEER: Selective Safety Steering for Moving Beyond Hard Refusals to Constructive Alternatives

ALTSTEER is an inference-time framework that couples selective intervention with refusal-anchored constructive redirection within a single inference pass, and uses an internal refusal-relevant signal to decide when to steer, and applies staged steering to shift generation from refusal-oriented control toward constructi...

Hoejoon Kwon, B. Lim, K. Kim et al. · 0 citations
Review Open access 2026

Narrative Consistency in Large Language Model-Generated Stories: A Survey

This survey examines the problem as narrative consistency, defined as the task-conditioned preservation of binding propositions in the operative narrative state, and introduces a four-category, fourteen-subtype taxonomy comprising World and Setting, Character-Agentive, Event-Structural, and Narration and Discourse cate...

Keunhyeung Park, Seunguk Yu, Jinhee Jang et al. · 0 citations

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