✨Anatomy of Agentic Memory: Taxonomy and Empirical Analysis of Evaluation and System Limitations

📝 Summary:
Agentic memory systems for LLM agents face empirical challenges including inadequate benchmarks, misaligned metrics, and performance variability that limit their practical effectiveness. AI-generated ...

🔹 Publication Date: Published on Feb 22

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.19320
• PDF: https://arxiv.org/pdf/2602.19320
• Github: https://github.com/FredJiang0324/Anatomy-of-Agentic-Memory

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✨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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