✨Agent Skills: A Data-Driven Analysis of Claude Skills for Extending Large Language Model Functionality

📝 Summary:
Agent skills extend large language model (LLM) agents with reusable, program-like modules that define triggering conditions, procedural logic, and tool interactions. As these skills proliferate in pub...

🔹 Publication Date: Published on Feb 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.08004
• PDF: https://arxiv.org/pdf/2602.08004

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✨CodeCircuit: Toward Inferring LLM-Generated Code Correctness via Attribution Graphs

📝 Summary:
CodeCircuit assesses LLM code correctness purely from its internal neural dynamics. It uses algorithmic attribution graphs to identify structural signatures of correct reasoning versus failure. This reliably predicts correctness and fixes errors.

🔹 Publication Date: Published on Feb 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.07080
• PDF: https://arxiv.org/pdf/2602.07080
• Github: https://github.com/bruno686/CodeCircuit

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✨Towards Agentic Intelligence for Materials Science

📝 Summary:
AI-driven materials science integrates large language models across discovery pipelines from data curation to agent-based experimentation, emphasizing system-level optimization and autonomous goal pur...

🔹 Publication Date: Published on Jan 29

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.00169
• PDF: https://arxiv.org/pdf/2602.00169

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✨Anchored Decoding: Provably Reducing Copyright Risk for Any Language Model

📝 Summary:
Anchored Decoding is an inference-time method that reduces verbatim copying in language models. It guides a risky LM with a permissively trained safe LM, significantly lowering copyright risk while preserving fluency and factuality. This method achieves up to 75% reduction in measurable copying.

🔹 Publication Date: Published on Feb 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.07120
• PDF: https://arxiv.org/pdf/2602.07120
• Project Page: https://tinyurl.com/anchored-decoding-demo
• Github: https://github.com/jacqueline-he/anchored-decoding

🔹 Models citing this paper:
• https://huggingface.co/jacquelinehe/tinycomma-1.8b-llama3-tokenizer

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✨Col-Bandit: Zero-Shot Query-Time Pruning for Late-Interaction Retrieval

📝 Summary:
Col-Bandit reduces computational costs in multi-vector late-interaction retrieval by adaptively pruning token-level interactions during query processing while maintaining ranking accuracy. AI-generate...

🔹 Publication Date: Published on Feb 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.02827
• PDF: https://arxiv.org/pdf/2602.02827
• Project Page: https://roipony.github.io/ColBandit/

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✨Reasoning-Augmented Representations for Multimodal Retrieval

📝 Summary:
The paper enhances Universal Multimodal Retrieval by decoupling reasoning from retrieval. It uses a Vision-Language Model to make implicit semantics explicit in both corpus entries and queries. Training the retriever on these reasoning-augmented representations yields consistent performance gains...

🔹 Publication Date: Published on Feb 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.07125
• PDF: https://arxiv.org/pdf/2602.07125
• Github: https://github.com/AugmentedRetrieval/ReasoningAugmentedRetrieval

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✨RLinf-USER: A Unified and Extensible System for Real-World Online Policy Learning in Embodied AI

📝 Summary:
USER is a unified system for scalable, asynchronous online policy learning in physical robots. It treats robots as hardware resources, manages communication, and supports diverse learning paradigms, including VLA models, enabling robust real-world AI training.

🔹 Publication Date: Published on Feb 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.07837
• PDF: https://arxiv.org/pdf/2602.07837
• Project Page: https://rlinf.readthedocs.io/en/latest/rst_source/publications/rlinf_user.html
• Github: https://github.com/RLinf/RLinf/blob/main/examples/embodiment/run_realworld_async.sh

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✨TermiGen: High-Fidelity Environment and Robust Trajectory Synthesis for Terminal Agents

📝 Summary:
TermiGen introduces a pipeline for generating verifiable terminal environments and resilient trajectories to improve open-weight LLMs' ability to execute complex tasks and recover from runtime errors....

🔹 Publication Date: Published on Feb 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.07274
• PDF: https://arxiv.org/pdf/2602.07274
• Github: https://github.com/ucsb-mlsec/terminal-bench-env

🔹 Models citing this paper:
• https://huggingface.co/UCSB-SURFI/TermiGen-32B

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✨UI-Venus-1.5 Technical Report

📝 Summary:
UI-Venus-1.5 is a unified GUI agent with improved performance through mid-training stages, online reinforcement learning, and model merging techniques. AI-generated summary GUI agents have emerged as ...

🔹 Publication Date: Published on Feb 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.09082
• PDF: https://arxiv.org/pdf/2602.09082
• Github: https://github.com/inclusionAI/UI-Venus

🔹 Models citing this paper:
• https://huggingface.co/inclusionAI/UI-Venus-1.5-8B
• https://huggingface.co/inclusionAI/UI-Venus-1.5-30B-A3B
• https://huggingface.co/inclusionAI/UI-Venus-1.5-2B

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✨SkillRL: Evolving Agents via Recursive Skill-Augmented Reinforcement Learning

📝 Summary:
SkillRL enables LLM agents to improve through hierarchical skill discovery and recursive policy evolution, achieving superior performance on complex tasks while reducing computational overhead. AI-gen...

🔹 Publication Date: Published on Feb 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.08234
• PDF: https://arxiv.org/pdf/2602.08234
• Github: https://github.com/aiming-lab/SkillRL

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✨Agent Banana: High-Fidelity Image Editing with Agentic Thinking and Tooling

📝 Summary:
Agent Banana addresses challenges in instruction-based image editing through a hierarchical framework with context folding and image layer decomposition for high-fidelity, multi-turn editing at ultra-...

🔹 Publication Date: Published on Feb 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.09084
• PDF: https://arxiv.org/pdf/2602.09084
• Project Page: https://agent-banana.github.io/
• Github: https://github.com/taco-group/agent-banana

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✨SCALE: Self-uncertainty Conditioned Adaptive Looking and Execution for Vision-Language-Action Models

📝 Summary:
SCALE is a novel inference strategy for Vision-Language-Action models that jointly modulates visual perception and action based on self-uncertainty, improving robustness without additional training or...

🔹 Publication Date: Published on Feb 4

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.04208
• PDF: https://arxiv.org/pdf/2602.04208
• Project Page: https://dcahn12.github.io/projects/scale/

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✨ANCHOR: Branch-Point Data Generation for GUI Agents

📝 Summary:
A trajectory expansion framework called Anchor bootstraps scalable desktop supervision from seed demonstrations by identifying branch points and generating new trajectories through state-grounded task...

🔹 Publication Date: Published on Feb 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.07153
• PDF: https://arxiv.org/pdf/2602.07153

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✨Prism: Spectral-Aware Block-Sparse Attention

📝 Summary:
Prism addresses inefficiencies in block-sparse attention for long-context LLM pre-filling by using a spectral-aware approach that improves block selection accuracy through energy-based temperature cal...

🔹 Publication Date: Published on Feb 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.08426
• PDF: https://arxiv.org/pdf/2602.08426
• Github: https://github.com/xinghaow99/prism

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✨Temporal Pair Consistency for Variance-Reduced Flow Matching

📝 Summary:
Temporal Pair Consistency reduces variance in continuous-time generative models by coupling velocity predictions at paired timesteps, improving sample quality and efficiency without altering model arc...

🔹 Publication Date: Published on Feb 4

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.04908
• PDF: https://arxiv.org/pdf/2602.04908

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✨Code2World: A GUI World Model via Renderable Code Generation

📝 Summary:
Code2World is a GUI world model that predicts next visual states by generating renderable code. It solves visual fidelity and structural control issues of prior methods, significantly boosting autonomous agent navigation performance.

🔹 Publication Date: Published on Feb 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.09856
• PDF: https://arxiv.org/pdf/2602.09856
• Project Page: https://amap-ml.github.io/Code2World/
• Github: https://github.com/AMAP-ML/Code2World

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✨Chain of Mindset: Reasoning with Adaptive Cognitive Modes

📝 Summary:
A novel training-free framework called Chain of Mindset enables step-level adaptive mindset orchestration for large language models by integrating spatial, convergent, divergent, and algorithmic reaso...

🔹 Publication Date: Published on Feb 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.10063
• PDF: https://arxiv.org/pdf/2602.10063
• Github: https://github.com/QuantaAlpha/chain-of-mindset

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✨VideoWorld 2: Learning Transferable Knowledge from Real-world Videos

📝 Summary:
VideoWorld 2 enables transferable knowledge learning from raw videos through a dynamic-enhanced Latent Dynamics Model that decouples action dynamics from visual appearance, achieving improved task per...

🔹 Publication Date: Published on Feb 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.10102
• PDF: https://arxiv.org/pdf/2602.10102
• Project Page: https://maverickren.github.io/VideoWorld2.github.io/
• Github: https://github.com/ByteDance-Seed/VideoWorld/tree/main/VideoWorld2

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✨BagelVLA: Enhancing Long-Horizon Manipulation via Interleaved Vision-Language-Action Generation

📝 Summary:
BagelVLA is a unified Vision-Language-Action model that integrates linguistic planning, visual forecasting, and action generation through residual flow guidance for improved manipulation tasks. AI-gen...

🔹 Publication Date: Published on Feb 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.09849
• PDF: https://arxiv.org/pdf/2602.09849
• Project Page: https://cladernyjorn.github.io/BagelVLA.github.io/

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✨DLLM-Searcher: Adapting Diffusion Large Language Model for Search Agents

📝 Summary:
Diffusion Large Language Models are optimized for search agents through enhanced reasoning capabilities and reduced latency via a parallel reasoning paradigm. AI-generated summary Recently, Diffusion ...

🔹 Publication Date: Published on Feb 3

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.07035
• PDF: https://arxiv.org/pdf/2602.07035
• Project Page: https://bubble65.github.io/dllm-searcher-pub/
• Github: https://github.com/bubble65/DLLM-Searcher

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✨Covo-Audio Technical Report

📝 Summary:
Covo-Audio is a 7B-parameter end-to-end large audio language model that processes continuous audio inputs and generates audio outputs, achieving state-of-the-art performance across speech-text modelin...

🔹 Publication Date: Published on Feb 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.09823
• PDF: https://arxiv.org/pdf/2602.09823

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