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arXiv:2602.17881v1 Announce Type: cross Abstract: Steering vectors are a lightweight method for controlling language model behavior by adding a learned bias to the activations at …
arXiv:2602.17905v1 Announce Type: cross Abstract: Interactive systems such as chatbots and games are increasingly used to persuade and educate on sustainability-related topics, yet it remains …
arXiv:2602.17907v1 Announce Type: cross Abstract: Traditional neural topic models are typically optimized by reconstructing the document's Bag-of-Words (BoW) representations, overlooking contextual information and struggling with …
arXiv:2602.17911v1 Announce Type: cross Abstract: Current biomedical question answering (QA) systems often assume that medical knowledge applies uniformly, yet real-world clinical reasoning is inherently conditional: …
arXiv:2602.17913v1 Announce Type: cross Abstract: Long-horizon agents often compress interaction histories into write-time summaries. This creates a fundamental write-before-query barrier: compression decisions are made before …
arXiv:2602.17930v1 Announce Type: cross Abstract: Reinforcement learning (RL) agents often suffer from high sample complexity in sparse or delayed reward settings due to limited prior …
arXiv:2602.17815v1 Announce Type: new Abstract: Neuroscience has uncovered a fundamental mechanism of our social nature: human brain activity becomes synchronized with others in many social …
arXiv:2602.17848v1 Announce Type: new Abstract: Recent work has shown that larger language models have better predictive power for eye movement and reading time data. While …
arXiv:2602.17937v1 Announce Type: new Abstract: Instruction optimization provides a lightweight, model-agnostic approach to enhancing the reasoning performance of large language models (LLMs). This paper presents …
arXiv:2602.17949v1 Announce Type: new Abstract: Background: Clinical named entity recognition tools commonly map free text to Unified Medical Language System (UMLS) Concept Unique Identifiers (CUIs). …
arXiv:2602.17981v1 Announce Type: new Abstract: Retrieval-augmented generation is increasingly used for financial question answering over long regulatory filings, yet reliability depends on retrieving the exact …
arXiv:2602.18029v1 Announce Type: new Abstract: Evaluation is no longer a final checkpoint in the machine learning lifecycle. As AI systems evolve from static models to …
