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arXiv:2602.12566v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) plays a key role in stimulating the explicit reasoning capability of Large Language Models …
arXiv:2602.12586v1 Announce Type: new Abstract: While plan-and-infill decoding in Masked Diffusion Models (MDMs) shows promise for mathematical and code reasoning, performance remains highly sensitive to …
arXiv:2602.12617v1 Announce Type: new Abstract: This paper presents GeoAgent, a model capable of reasoning closely with humans and deriving fine-grained address conclusions. Previous RL-based methods …
arXiv:2602.12631v1 Announce Type: new Abstract: Inventory control is a fundamental operations problem in which ordering decisions are traditionally guided by theoretically grounded operations research (OR) …
arXiv:2602.12662v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as autonomous agents for multi-turn decision-making tasks. However, current agents typically rely on …
arXiv:2602.12665v1 Announce Type: new Abstract: Logic provides a controlled testbed for evaluating LLM-based reasoners, yet standard SAT-style benchmarks often conflate surface difficulty (length, wording, clause …
arXiv:2602.12748v1 Announce Type: new Abstract: The explainable AI (XAI) research community has proposed numerous technical methods, yet deploying explainability as systems remains challenging: Interactive explanation …
arXiv:2602.12852v1 Announce Type: new Abstract: Deep Research systems based on web agents have shown strong potential in solving complex information-seeking tasks, yet their search efficiency …
arXiv:2602.12963v1 Announce Type: new Abstract: An important question in the field of AI is the extent to which successful behaviour requires an internal representation of …
arXiv:2602.13093v2 Announce Type: new Abstract: Large reasoning models with reasoning capabilities achieve state-of-the-art performance on complex tasks, but their robustness under multi-turn adversarial pressure remains …
arXiv:2602.13166v1 Announce Type: new Abstract: This paper presents a hybrid obstacle avoidance architecture that integrates Optimal Control under clearance with a Fuzzy Rule Based System …
arXiv:2511.13494v1 Announce Type: cross Abstract: Recent vision-language models (VLMs) such as CLIP, OpenCLIP, EVA02-CLIP and SigLIP achieve strong zero-shot performance, but it is unclear how …