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arXiv:2603.18656v1 Announce Type: new Abstract: Multimodal reasoning in vision-language models (VLMs) typically relies on a two-stage process: supervised fine-tuning (SFT) and reinforcement learning (RL). In …
arXiv:2603.18633v1 Announce Type: new Abstract: The rapid evolution of artificial intelligence, from task-specific systems to foundation models exhibiting broad, flexible competence across reasoning, creative synthesis, …
arXiv:2603.18631v1 Announce Type: new Abstract: Driven by the development of persistent, self-adapting autonomous agents, equipping these systems with high-fidelity memory access for long-horizon reasoning has …
arXiv:2603.18627v1 Announce Type: new Abstract: Precise Text-to-Image (T2I) generation has achieved great success but is hindered by the limited relational reasoning of static text encoders …
arXiv:2603.18614v1 Announce Type: new Abstract: Tool-augmented large language models (LLMs) must tightly couple multi-step reasoning with external actions, yet existing benchmarks often confound this interplay …
arXiv:2603.18577v1 Announce Type: new Abstract: Text-guided image editors can now manipulate authentic medical scans with high fidelity, enabling lesion implantation/removal that threatens clinical trust and …
arXiv:2603.18573v1 Announce Type: new Abstract: Training conversational recommender systems (CRS) requires extensive dialogue data, which is challenging to collect at scale. To address this, researchers …
arXiv:2603.18571v1 Announce Type: new Abstract: Subcellular localization is a crucial biological task for drug target identification and function annotation. Although it has been biologically realized …
arXiv:2603.18563v1 Announce Type: new Abstract: AI agents are increasingly deployed in interactive economic environments characterized by repeated AI-AI interactions. Despite AI agents' advanced capabilities, empirical …
arXiv:2603.18528v1 Announce Type: new Abstract: Text-to-image models produce images that align well with natural language prompts, but compositional generation has long been a central challenge. …
arXiv:2603.18507v1 Announce Type: new Abstract: Persona prompting can steer LLM generation towards a domain-specific tone and pattern. This behavior enables use cases in multi-agent systems …
arXiv:2603.18495v1 Announce Type: new Abstract: Recent advances in Vision-Language Models (VLMs) have enabled video-instructed robotic programming, allowing agents to interpret video demonstrations and generate executable …
