✨TRUST-SQL: Tool-Integrated Multi-Turn Reinforcement Learning for Text-to-SQL over Unknown Schemas

📝 Summary:
TRUST-SQL addresses unknown schema Text-to-SQL by employing a four-phase protocol and a Dual-Track GRPO strategy. This resolves credit assignment, achieving significant performance gains and matching baselines without pre-loaded metadata.

🔹 Publication Date: Published on Mar 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.16448
• PDF: https://arxiv.org/pdf/2603.16448

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✨Thinking in Uncertainty: Mitigating Hallucinations in MLRMs with Latent Entropy-Aware Decoding

📝 Summary:
Recent advancements in multimodal large reasoning models (MLRMs) have significantly improved performance in visual question answering. However, we observe that transition words (e.g., because, however...

🔹 Publication Date: Published on Mar 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.13366
• PDF: https://arxiv.org/pdf/2603.13366
• Project Page: https://mlrm-lead.github.io/
• Github: https://github.com/mlrm-LEAD/mlrm-LEAD

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✨FinToolBench: Evaluating LLM Agents for Real-World Financial Tool Use

📝 Summary:
FinToolBench presents the first real-world benchmark for evaluating financial tool learning agents, featuring 760 executable tools and comprehensive evaluation criteria beyond simple execution success...

🔹 Publication Date: Published on Mar 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.08262
• PDF: https://arxiv.org/pdf/2603.08262
• Github: https://github.com/Double-wk/FinToolBench

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✨One-Eval: An Agentic System for Automated and Traceable LLM Evaluation

📝 Summary:
One-Eval is an agentic evaluation system that automates large language model assessment by converting natural-language requests into executable workflows with integrated benchmark planning, dataset ha...

🔹 Publication Date: Published on Mar 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.09821
• PDF: https://arxiv.org/pdf/2603.09821
• Project Page: https://github.com/OpenDCAI/One-Eval
• Github: https://github.com/OpenDCAI/One-Eval

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✨SK-Adapter: Skeleton-Based Structural Control for Native 3D Generation

📝 Summary:
SK-Adapter enables precise 3D structural control by treating skeletons as direct inputs through a lightweight adapter network that injects learnable tokens into frozen 3D generation models via cross-a...

🔹 Publication Date: Published on Mar 14

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.14152
• PDF: https://arxiv.org/pdf/2603.14152
• Project Page: https://sk-adapter.github.io/
• Github: https://github.com/sk-adapter/SK-Adapter

==================================

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✨InCoder-32B: Code Foundation Model for Industrial Scenarios

📝 Summary:
InCoder-32B is a 32-billion-parameter code model for industrial programming tasks like chip design and GPU optimization. It was trained with extended context and execution verification, achieving strong performance on industrial benchmarks and competitive results on general tasks.

🔹 Publication Date: Published on Mar 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.16790
• PDF: https://arxiv.org/pdf/2603.16790
• Project Page: https://huggingface.co/Multilingual-Multimodal-NLP/IndustrialCoder
• Github: https://github.com/CSJianYang/Industrial-Coder

==================================

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✨Semi-Autonomous Formalization of the Vlasov-Maxwell-Landau Equilibrium

📝 Summary:
We present a complete Lean 4 formalization of the equilibrium characterization in the Vlasov-Maxwell-Landau (VML) system, which describes the motion of charged plasma. The project demonstrates the ful...

🔹 Publication Date: Published on Mar 16

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.15929
• PDF: https://arxiv.org/pdf/2603.15929
• Project Page: https://github.com/Vilin97/Clawristotle
• Github: https://github.com/Vilin97/Clawristotle

==================================

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✨From Passive Observer to Active Critic: Reinforcement Learning Elicits Process Reasoning for Robotic Manipulation

📝 Summary:
Accurate process supervision remains a critical challenge for long-horizon robotic manipulation. A primary bottleneck is that current video MLLMs, trained primarily under a Supervised Fine-Tuning (SFT...

🔹 Publication Date: Published on Mar 16

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.15600
• PDF: https://arxiv.org/pdf/2603.15600
• Project Page: https://huggingface.co/collections/LeonOverload/primo-r1

🔹 Models citing this paper:
• https://huggingface.co/LeonOverload/PRIMO-R1-7B
• https://huggingface.co/LeonOverload/PRIMO-COT-SFT-7B

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✨Anticipatory Planning for Multimodal AI Agents

📝 Summary:
TraceR1 is a two-stage reinforcement learning framework for multimodal AI agents. It enhances planning by training anticipatory trajectory reasoning to forecast future actions and refine them with execution feedback. This significantly improves planning stability, execution robustness, and genera...

🔹 Publication Date: Published on Mar 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.16777
• PDF: https://arxiv.org/pdf/2603.16777

==================================

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✨ViT-AdaLA: Adapting Vision Transformers with Linear Attention

📝 Summary:
ViT-AdaLA adapts vision foundation models to linear attention Vision Transformers through attention alignment, feature alignment, and supervised fine-tuning to overcome quadratic complexity limitation...

🔹 Publication Date: Published on Mar 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.16063
• PDF: https://arxiv.org/pdf/2603.16063

==================================

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