✨Dr. Zero: Self-Evolving Search Agents without Training Data

📝 Summary:
A data-free self-evolution framework enables large language models to autonomously improve reasoning capabilities through iterative question generation and solving, achieving performance comparable to...

🔹 Publication Date: Published on Jan 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.07055
• PDF: https://arxiv.org/pdf/2601.07055
• Github: https://github.com/facebookresearch/drzero

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

For more data science resources:
✓ https://t.me/DataScienceT

#AI #DataScience #MachineLearning #HuggingFace #Research

✨GlimpRouter: Efficient Collaborative Inference by Glimpsing One Token of Thoughts

📝 Summary:
Large reasoning models' inference latency can be reduced by routing reasoning steps to larger models based on the entropy of their first token, enabling efficient collaborative inference without addit...

🔹 Publication Date: Published on Jan 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.05110
• PDF: https://arxiv.org/pdf/2601.05110
• Github: https://github.com/Zengwh02/GlimpRouter

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

For more data science resources:
✓ https://t.me/DataScienceT

#AI #DataScience #MachineLearning #HuggingFace #Research

✨OpenTinker: Separating Concerns in Agentic Reinforcement Learning

📝 Summary:
OpenTinker provides a modular infrastructure for reinforcement learning of large language model agents with separated components and managed execution runtime. AI-generated summary We introduce OpenTi...

🔹 Publication Date: Published on Jan 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/pdf/2601.07376
• PDF: https://arxiv.org/pdf/2601.07376
• Project Page: https://open-tinker.github.io/opentinker-page/
• Github: https://github.com/open-tinker/OpenTinker

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

For more data science resources:
✓ https://t.me/DataScienceT

#AI #DataScience #MachineLearning #HuggingFace #Research

✨On the Fallacy of Global Token Perplexity in Spoken Language Model Evaluation

📝 Summary:
Speech models trained on raw audio can generate appropriate content while maintaining speaker and emotion attributes, but traditional text-based evaluation methods underestimate speech characteristics...

🔹 Publication Date: Published on Jan 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.06329
• PDF: https://arxiv.org/pdf/2601.06329

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

For more data science resources:
✓ https://t.me/DataScienceT

#AI #DataScience #MachineLearning #HuggingFace #Research

✨Are LLM Decisions Faithful to Verbal Confidence?

📝 Summary:
Large language models exhibit a disconnect between their expressed uncertainty and strategic decision-making under varying penalty conditions, failing to adjust abstention policies even when optimal. ...

🔹 Publication Date: Published on Jan 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.07767
• PDF: https://arxiv.org/pdf/2601.07767

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

For more data science resources:
✓ https://t.me/DataScienceT

#AI #DataScience #MachineLearning #HuggingFace #Research

✨Codified Foreshadowing-Payoff Text Generation

📝 Summary:
Large language models struggle with maintaining long-range narrative dependencies, but a new framework called CFPG addresses this by structuring narrative continuity through executable causal predicat...

🔹 Publication Date: Published on Jan 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.07033
• PDF: https://arxiv.org/pdf/2601.07033

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

For more data science resources:
✓ https://t.me/DataScienceT

#AI #DataScience #MachineLearning #HuggingFace #Research

✨Controllable Memory Usage: Balancing Anchoring and Innovation in Long-Term Human-Agent Interaction

📝 Summary:
This paper presents SteeM, a framework for dynamically regulating memory reliance in LLM agents. It allows users to balance innovation with historical fidelity, overcoming the all-or-nothing problem of memory use. This approach outperforms conventional methods for personalized human-agent interac...

🔹 Publication Date: Published on Jan 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.05107
• PDF: https://arxiv.org/pdf/2601.05107

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

For more data science resources:
✓ https://t.me/DataScienceT

#LLM #AI #HumanAgentInteraction #Memory #MachineLearning

✨"TODO: Fix the Mess Gemini Created": Towards Understanding GenAI-Induced Self-Admitted Technical Debt

📝 Summary:
Developers admit technical debt GIST in AI-assisted code, often due to postponed testing, incomplete adaptation, and limited understanding. This debt emerges when incorporating AI-generated code despite developer uncertainty about its behavior or correctness.

🔹 Publication Date: Published on Jan 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.07786
• PDF: https://arxiv.org/pdf/2601.07786

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

For more data science resources:
✓ https://t.me/DataScienceT

#AI #DataScience #MachineLearning #HuggingFace #Research

✨OS-Symphony: A Holistic Framework for Robust and Generalist Computer-Using Agent

📝 Summary:
OS-Symphony is a framework enhancing computer-using agents with robustness and generalization. It features a Reflection-Memory Agent for self-correction and a Multimodal Searcher for visually aligned tutorials. This achieved state-of-the-art results on online benchmarks, including 65.84% on OSWorld.

🔹 Publication Date: Published on Jan 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.07779
• PDF: https://arxiv.org/pdf/2601.07779
• Project Page: https://os-copilot.github.io/OS-Symphony
• Github: https://github.com/OS-Copilot/OS-Symphony

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

For more data science resources:
✓ https://t.me/DataScienceT

#AI #DataScience #MachineLearning #HuggingFace #Research

✨MHLA: Restoring Expressivity of Linear Attention via Token-Level Multi-Head

📝 Summary:
Multi-Head Linear Attention addresses the performance degradation in linear attention by preserving representational diversity through head-wise token dimension computation, maintaining linear complex...

🔹 Publication Date: Published on Jan 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.07832
• PDF: https://arxiv.org/pdf/2601.07832
• Project Page: https://dagroup-pku.github.io/MHLA/
• Github: https://github.com/DAGroup-PKU/MHLA

🔹 Models citing this paper:
• https://huggingface.co/DAGroup-PKU/MHLA

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

For more data science resources:
✓ https://t.me/DataScienceT

#AI #DataScience #MachineLearning #HuggingFace #Research