✨TIC-VLA: A Think-in-Control Vision-Language-Action Model for Robot Navigation in Dynamic Environments

📝 Summary:
TIC-VLA is a latency-aware framework enhancing robot navigation by explicitly modeling delayed semantic reasoning. It uses a delayed semantic-control interface and latency-consistent training. This allows robots to maintain real-time control despite significant reasoning delays.

🔹 Publication Date: Published on Feb 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.02459
• PDF: https://arxiv.org/pdf/2602.02459
• Project Page: https://ucla-mobility.github.io/TIC-VLA/
• Github: https://github.com/ucla-mobility/TIC-VLA

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✨From Features to Actions: Explainability in Traditional and Agentic AI Systems

📝 Summary:
This paper compares static and agentic AI explainability. It finds attribution methods reliable for static predictions but not for diagnosing failures in multi-step agentic systems. Trace-based diagnostics effectively localize agentic breakdowns, urging a shift to trajectory-level explainability.

🔹 Publication Date: Published on Feb 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.06841
• PDF: https://arxiv.org/pdf/2602.06841
• Project Page: https://vectorinstitute.github.io/unified-xai-evaluation-framework/
• Github: https://github.com/VectorInstitute/unified-xai-evaluation-framework

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✨GigaBrain-0.5M*: a VLA That Learns From World Model-Based Reinforcement Learning

📝 Summary:
GigaBrain-0.5M enhances vision-language-action models by integrating world model-based reinforcement learning. This improves performance by 30% on complex robotic tasks and enables reliable long-horizon execution, overcoming prior VLA limitations.

🔹 Publication Date: Published on Feb 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.12099
• PDF: https://arxiv.org/pdf/2602.12099
• Project Page: https://gigabrain05m.github.io/

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

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✨Learning beyond Teacher: Generalized On-Policy Distillation with Reward Extrapolation

📝 Summary:
On-policy distillation is extended through a generalized framework that introduces flexible reference models and reward scaling factors, demonstrating improved performance through reward extrapolation...

🔹 Publication Date: Published on Feb 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.12125
• PDF: https://arxiv.org/pdf/2602.12125
• Github: https://github.com/RUCBM/G-OPD

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✨Unveiling Implicit Advantage Symmetry: Why GRPO Struggles with Exploration and Difficulty Adaptation

📝 Summary:
Asymmetric Group Relative Advantage Estimation addresses exploration and difficulty adaptation challenges in reinforcement learning with large language models by dynamically modulating exploration inc...

🔹 Publication Date: Published on Feb 5

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.05548
• PDF: https://arxiv.org/pdf/2602.05548
• Github: https://github.com/HKU-HealthAI/A-GRAE

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✨Budget-Constrained Agentic Large Language Models: Intention-Based Planning for Costly Tool Use

📝 Summary:
Budget-constrained tool-augmented agents use a hierarchical world model and intent-aware planning to optimize multi-step task completion under monetary constraints. AI-generated summary We study budge...

🔹 Publication Date: Published on Feb 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.11541
• PDF: https://arxiv.org/pdf/2602.11541

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

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✨Dreaming in Code for Curriculum Learning in Open-Ended Worlds

📝 Summary:
Foundation models generate executable environment code to scaffold learning progress in open-ended worlds, enabling agents to acquire long-horizon skills through curriculum control. AI-generated summa...

🔹 Publication Date: Published on Feb 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.08194
• PDF: https://arxiv.org/pdf/2602.08194
• Project Page: https://konstantinosmitsides.github.io/dreaming-in-code
• Github: https://github.com/konstantinosmitsides/dreaming-in-code

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

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✨Neural Additive Experts: Context-Gated Experts for Controllable Model Additivity

📝 Summary:
Neural Additive Experts combines multiple specialized networks with a dynamic gating mechanism to balance predictive accuracy and feature interpretability in machine learning models. AI-generated summ...

🔹 Publication Date: Published on Feb 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.10585
• PDF: https://arxiv.org/pdf/2602.10585
• Github: https://github.com/Teddy-XiongGZ/NAE

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✨The Devil Behind Moltbook: Anthropic Safety is Always Vanishing in Self-Evolving AI Societies

📝 Summary:
Multi-agent LLM systems cannot achieve continuous self-improvement and maintain safety if isolated. Isolated self-evolution causes statistical blind spots, leading to irreversible safety degradation. This is a fundamental limit, requiring external oversight or new safety mechanisms.

🔹 Publication Date: Published on Feb 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.09877
• PDF: https://arxiv.org/pdf/2602.09877

✨ Datasets citing this paper:
• https://huggingface.co/datasets/xunyoyo/Self-Evolving-Safety

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✨LawThinker: A Deep Research Legal Agent in Dynamic Environments

📝 Summary:
LawThinker is an autonomous legal research agent that uses an Explore-Verify-Memorize strategy with a DeepVerifier module to ensure accurate and procedurally compliant legal reasoning through dynamic ...

🔹 Publication Date: Published on Feb 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.12056
• PDF: https://arxiv.org/pdf/2602.12056
• Github: https://github.com/yxy-919/LawThinker-agent

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✨Voxtral Realtime

📝 Summary:
Voxtral Realtime is a streaming speech recognition model trained end-to-end for sub-second latency with performance matching offline systems. AI-generated summary We introduce Voxtral Realtime, a nati...

🔹 Publication Date: Published on Feb 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.11298
• PDF: https://arxiv.org/pdf/2602.11298
• Project Page: https://mistral.ai/news/voxtral-transcribe-2

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✨dVoting: Fast Voting for dLLMs

📝 Summary:
Diffusion large language models enable parallel token generation and efficient reasoning enhancement through a voting technique that identifies and refines uncertain predictions across multiple sample...

🔹 Publication Date: Published on Feb 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.12153
• PDF: https://arxiv.org/pdf/2602.12153
• Github: https://github.com/fscdc/dVoting

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✨ThinkRouter: Efficient Reasoning via Routing Thinking between Latent and Discrete Spaces

📝 Summary:
ThinkRouter is a confidence-aware routing mechanism that improves reasoning efficiency by switching between discrete token and latent spaces based on model confidence, achieving better accuracy and fa...

🔹 Publication Date: Published on Feb 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.11683
• PDF: https://arxiv.org/pdf/2602.11683

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

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✨ScalSelect: Scalable Training-Free Multimodal Data Selection for Efficient Visual Instruction Tuning

📝 Summary:
ScalSelect is a scalable training-free method for selecting representative multimodal data that achieves near-full-dataset performance with significantly reduced computational requirements. AI-generat...

🔹 Publication Date: Published on Feb 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.11636
• PDF: https://arxiv.org/pdf/2602.11636
• Github: https://github.com/ChangtiWu/ScalSelect

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

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✨MolmoSpaces: A Large-Scale Open Ecosystem for Robot Navigation and Manipulation

📝 Summary:
MolmoSpaces presents an open ecosystem with diverse indoor environments and annotated objects for large-scale robot policy benchmarking across multiple tasks and simulators. AI-generated summary Deplo...

🔹 Publication Date: Published on Feb 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.11337
• PDF: https://arxiv.org/pdf/2602.11337
• Project Page: https://allenai.org/blog/molmospaces
• Github: https://github.com/allenai/molmospaces

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✨Gaia2: Benchmarking LLM Agents on Dynamic and Asynchronous Environments

📝 Summary:
Gaia2 presents a benchmark for evaluating large language model agents in asynchronous, dynamic environments with temporal constraints and multi-agent collaboration, featuring a write-action verifier f...

🔹 Publication Date: Published on Feb 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.11964
• PDF: https://arxiv.org/pdf/2602.11964

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✨MiniCPM-SALA: Hybridizing Sparse and Linear Attention for Efficient Long-Context Modeling

📝 Summary:
MiniCPM-SALA combines sparse and linear attention mechanisms in a hybrid architecture to enable efficient processing of ultra-long contexts while maintaining model performance and reducing training co...

🔹 Publication Date: Published on Feb 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.11761
• PDF: https://arxiv.org/pdf/2602.11761
• Github: https://github.com/OpenBMB/MiniCPM

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✨ABot-N0: Technical Report on the VLA Foundation Model for Versatile Embodied Navigation

📝 Summary:
A unified Vision-Language-Action model with a hierarchical architecture combining semantic reasoning and continuous trajectory generation achieves state-of-the-art performance across multiple embodied...

🔹 Publication Date: Published on Feb 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.11598
• PDF: https://arxiv.org/pdf/2602.11598
• Project Page: https://amap-cvlab.github.io/ABot-Navigation/ABot-N0/
• Github: https://github.com/amap-cvlab/ABot-Navigation/tree/ABot-N0

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✨Stroke of Surprise: Progressive Semantic Illusions in Vector Sketching

📝 Summary:
Progressive Semantic Illusions use a generative framework with dual-branch Score Distillation Sampling to create vector sketches that transform semantically through sequential stroke additions, achiev...

🔹 Publication Date: Published on Feb 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.12280
• PDF: https://arxiv.org/pdf/2602.12280
• Project Page: https://stroke-of-surprise.github.io/
• Github: https://github.com/stroke-of-surprise/Stroke-Of-Surprise

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✨MOSS-Audio-Tokenizer: Scaling Audio Tokenizers for Future Audio Foundation Models

📝 Summary:
A fully end-to-end Transformer-based audio tokenizer architecture achieves high-fidelity reconstruction across diverse audio domains and enables superior text-to-speech and automatic speech recognitio...

🔹 Publication Date: Published on Feb 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.10934
• PDF: https://arxiv.org/pdf/2602.10934
• Github: https://github.com/OpenMOSS/MOSS-Audio-Tokenizer

🔹 Models citing this paper:
• https://huggingface.co/OpenMOSS-Team/MOSS-Audio-Tokenizer

✨ Spaces citing this paper:
• https://huggingface.co/spaces/OpenMOSS-Team/MOSS-TTSD

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✨Sci-CoE: Co-evolving Scientific Reasoning LLMs via Geometric Consensus with Sparse Supervision

📝 Summary:
Sci-CoE is a two-stage scientific co-evolving framework that enables large language models to self-evolve as both solver and verifier through sparse-to-unsupervised learning transitions, improving sci...

🔹 Publication Date: Published on Feb 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.12164
• PDF: https://arxiv.org/pdf/2602.12164

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