✨Decoding ML Decision: An Agentic Reasoning Framework for Large-Scale Ranking System

📝 Summary:
GEARS presents a framework that reframes ranking optimization as an autonomous discovery process using specialized agent skills and validation hooks to balance algorithmic signals with ranking context...

🔹 Publication Date: Published on Feb 20

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.18640
• PDF: https://arxiv.org/pdf/2602.18640

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✨SimToolReal: An Object-Centric Policy for Zero-Shot Dexterous Tool Manipulation

📝 Summary:
SimToolReal enables generalizable robot manipulation of diverse tools through procedural simulation and universal reinforcement learning policies without task-specific training. AI-generated summary T...

🔹 Publication Date: Published on Feb 18

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.16863
• PDF: https://arxiv.org/pdf/2602.16863
• Project Page: https://simtoolreal.github.io/
• Github: https://github.com/tylerlum/simtoolreal

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✨On the "Induction Bias" in Sequence Models

📝 Summary:
Transformers require exponentially more data than RNNs for state tracking tasks. They also fail to share learned mechanisms across different sequence lengths, unlike RNNs which exhibit effective amortized learning by sharing weights. This reveals a fundamental in-distribution challenge for transf...

🔹 Publication Date: Published on Feb 20

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.18333
• PDF: https://arxiv.org/pdf/2602.18333

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✨Ani3DHuman: Photorealistic 3D Human Animation with Self-guided Stochastic Sampling

📝 Summary:
Ani3DHuman generates photorealistic 3D human animations by merging kinematics and video diffusion. It uses a layered motion representation and a novel self-guided stochastic sampling method to ensure photorealistic non-rigid motion and identity preservation.

🔹 Publication Date: Published on Feb 22

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.19089
• PDF: https://arxiv.org/pdf/2602.19089
• Github: https://github.com/qiisun/ani3dhuman

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✨From Perception to Action: An Interactive Benchmark for Vision Reasoning

📝 Summary:
Current vision-language models struggle with physical structures and causal constraints for complex 3D tasks. The new CHAIN benchmark evaluates this capability, revealing that state-of-the-art models still fail to plan effective actions based on perceived physical structure.

🔹 Publication Date: Published on Feb 24

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.21015
• PDF: https://arxiv.org/pdf/2602.21015
• Project Page: https://social-ai-studio.github.io/CHAIN/
• Github: https://social-ai-studio.github.io/CHAIN/

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✨PyVision-RL: Forging Open Agentic Vision Models via RL

📝 Summary:
PyVision-RL framework addresses interaction collapse in multimodal models through enhanced reinforcement learning techniques and efficient video processing strategies. AI-generated summary Reinforceme...

🔹 Publication Date: Published on Feb 24

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.20739
• PDF: https://arxiv.org/pdf/2602.20739
• Project Page: https://agent-x.space/pyvision-rl/
• Github: https://github.com/agents-x-project/PyVision-RL

🔹 Models citing this paper:
• https://huggingface.co/Agents-X/PyVision-Image-7B-SFT
• https://huggingface.co/Agents-X/PyVision-Image-7B-RL
• https://huggingface.co/Agents-X/PyVision-Video-7B-RL

✨ Datasets citing this paper:
• https://huggingface.co/datasets/Agents-X/PyVision-Image-SFT-Data
• https://huggingface.co/datasets/Agents-X/PyVision-Video-RL-Data
• https://huggingface.co/datasets/Agents-X/PyVision-Image-RL-Data

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✨LongCLI-Bench: A Preliminary Benchmark and Study for Long-horizon Agentic Programming in Command-Line Interfaces

📝 Summary:
LongCLI-Bench evaluates AI agents' ability to complete complex, multi-step programming tasks through command-line interfaces with detailed failure analysis and human-agent collaboration insights. AI-g...

🔹 Publication Date: Published on Feb 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.14337
• PDF: https://arxiv.org/pdf/2602.14337
• Project Page: https://github.com/finyorko/longcli-bench
• Github: https://github.com/finyorko/longcli-bench

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✨Conv-FinRe: A Conversational and Longitudinal Benchmark for Utility-Grounded Financial Recommendation

📝 Summary:
A new conversational financial recommendation benchmark evaluates large language models' ability to balance rational decision-making with user behavior alignment using multi-view references derived fr...

🔹 Publication Date: Published on Feb 19

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.16990
• PDF: https://arxiv.org/pdf/2602.16990
• Github: https://github.com/The-FinAI/Conv-FinRe

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✨FlowPrefill: Decoupling Preemption from Prefill Scheduling Granularity to Mitigate Head-of-Line Blocking in LLM Serving

📝 Summary:
FlowPrefill addresses head-of-line blocking in large language model serving by decoupling preemption granularity from scheduling frequency through operator-level preemption and event-driven scheduling...

🔹 Publication Date: Published on Feb 18

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.16603
• PDF: https://arxiv.org/pdf/2602.16603
• Github: https://github.com/HSIEHCHIACHI/FlowPrefill

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✨The Art of Efficient Reasoning: Data, Reward, and Optimization

📝 Summary:
Large language models benefit from scaled chain-of-thought reasoning through efficient training methods that balance trajectory length and accuracy using reinforcement learning with reward shaping. AI...

🔹 Publication Date: Published on Feb 24

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.20945
• PDF: https://arxiv.org/pdf/2602.20945

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✨Implicit Intelligence -- Evaluating Agents on What Users Don't Say

📝 Summary:
AI agents struggle to interpret implicitly specified real-world requests that require contextual reasoning beyond explicit instructions, as demonstrated by an evaluation framework using interactive YA...

🔹 Publication Date: Published on Feb 23

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.20424
• PDF: https://arxiv.org/pdf/2602.20424

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✨On Data Engineering for Scaling LLM Terminal Capabilities

📝 Summary:
Researchers developed a synthetic task generation pipeline and analyzed data strategies to improve terminal agent performance, creating a large-scale dataset and models that outperform larger counterp...

🔹 Publication Date: Published on Feb 24

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.21193
• PDF: https://arxiv.org/pdf/2602.21193
• Project Page: https://huggingface.co/collections/nvidia/nemotron-terminal

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✨Learning from Trials and Errors: Reflective Test-Time Planning for Embodied LLMs

📝 Summary:
Reflective Test-Time Planning enhances robot decision-making by integrating multiple reflection mechanisms that enable learning from experience and improving long-horizon task performance. AI-generate...

🔹 Publication Date: Published on Feb 24

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.21198
• PDF: https://arxiv.org/pdf/2602.21198
• Project Page: https://reflective-test-time-planning.github.io/

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✨Aletheia tackles FirstProof autonomously

📝 Summary:
We report the performance of Aletheia (Feng et al., 2026b), a mathematics research agent powered by Gemini 3 Deep Think, on the inaugural FirstProof challenge. Within the allowed timeframe of the chal...

🔹 Publication Date: Published on Feb 24

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.21201
• PDF: https://arxiv.org/pdf/2602.21201
• Project Page: https://github.com/google-deepmind/superhuman/tree/main/aletheia

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✨The Diffusion Duality, Chapter II: Ψ-Samplers and Efficient Curriculum

📝 Summary:
Discrete diffusion models with predictor-corrector samplers surpass traditional methods in generation quality and efficiency, challenging assumptions about masked diffusion's necessity in language mod...

🔹 Publication Date: Published on Feb 24

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.21185
• PDF: https://arxiv.org/pdf/2602.21185
• Project Page: https://s-sahoo.com/duo-ch2/

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✨Test-Time Training with KV Binding Is Secretly Linear Attention

📝 Summary:
This paper reinterprets Test-Time Training TTT with KV binding. Instead of memorization, it shows TTT is a form of learned linear attention with enhanced representational capacity. This new perspective explains puzzling behaviors, simplifies architectures, and boosts efficiency.

🔹 Publication Date: Published on Feb 24

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.21204
• PDF: https://arxiv.org/pdf/2602.21204
• Project Page: https://research.nvidia.com/labs/sil/projects/tttla/

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✨Generative AI and Machine Learning Collaboration for Container Dwell Time Prediction via Data Standardization

📝 Summary:
A collaborative framework integrating generative artificial intelligence with machine learning improves container dwell time prediction by standardizing unstructured text data, leading to reduced reha...

🔹 Publication Date: Published on Feb 24

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.20540
• PDF: https://arxiv.org/pdf/2602.20540

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✨DREAM: Deep Research Evaluation with Agentic Metrics

📝 Summary:
Deep Research Agents generate analyst-grade reports, yet evaluating them remains challenging due to the absence of a single ground truth and the multidimensional nature of research quality. Recent ben...

🔹 Publication Date: Published on Feb 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.18940
• PDF: https://arxiv.org/pdf/2602.18940

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✨Untied Ulysses: Memory-Efficient Context Parallelism via Headwise Chunking

📝 Summary:
UPipe enables efficient processing of long sequences in Transformer models through fine-grained chunking at the attention head level, significantly reducing activation memory usage while maintaining t...

🔹 Publication Date: Published on Feb 24

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.21196
• PDF: https://arxiv.org/pdf/2602.21196
• Project Page: https://rghadia.github.io/untied_ulysses_proj/
• Github: https://github.com/togethercomputer/Untied-Ulysses

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✨OCR-Agent: Agentic OCR with Capability and Memory Reflection

📝 Summary:
A novel iterative self-correction framework enhances vision-language models' reasoning robustness through capability reflection and memory reflection mechanisms, achieving superior performance on visu...

🔹 Publication Date: Published on Feb 24

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.21053
• PDF: https://arxiv.org/pdf/2602.21053
• Github: https://github.com/AIGeeksGroup/OCR-Agent

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