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arXiv:2602.22583v1 Announce Type: new Abstract: Example-based guidance is widely used to improve mathematical reasoning at inference time, yet its effectiveness is highly unstable across problems …
arXiv:2602.22585v1 Announce Type: new Abstract: Human evaluations play a central role in training and assessing AI models, yet these data are rarely treated as measurements …
arXiv:2602.22603v1 Announce Type: new Abstract: Long-running agentic tasks, such as deep research, require multi-hop reasoning over information distributed across multiple webpages and documents. In such …
arXiv:2602.22638v1 Announce Type: new Abstract: Route-planning agents powered by large language models (LLMs) have emerged as a promising paradigm for supporting everyday human mobility through …
arXiv:2602.22650v1 Announce Type: new Abstract: In online advertising, the inherent complexity and dynamic nature of advertising environments necessitate the use of auto-bidding services to assist …
arXiv:2602.22680v1 Announce Type: new Abstract: Large language models have enabled agents that reason, plan, and interact with tools and environments to accomplish complex tasks. As …
arXiv:2602.22702v1 Announce Type: new Abstract: Existing neural network calibration methods often treat calibration as a static, post-hoc optimization task. However, this neglects the dynamic and …
arXiv:2602.22718v1 Announce Type: new Abstract: Reinforcement Learning from Human Feedback (RLHF) has been widely applied to Large Language Model (LLM) post-training to align model outputs …
arXiv:2602.22743v1 Announce Type: new Abstract: Recommendation model performance is intrinsically tied to the quality, volume, and relevance of their training data. To address common challenges …
arXiv:2602.22751v1 Announce Type: new Abstract: Large reasoning models (LRMs) have emerged as a powerful paradigm for solving complex real-world tasks. In practice, these models are …
arXiv:2602.22758v1 Announce Type: new Abstract: We decompose physician disagreement in the HealthBench medical AI evaluation dataset to understand where variance resides and what observable features …
arXiv:2602.22769v1 Announce Type: new Abstract: Large Language Models (LLMs) are deployed as autonomous agents in increasingly complex applications, where enabling long-horizon memory is critical for …