✨Statistical Learning Theory in Lean 4: Empirical Processes from Scratch

📝 Summary:
A comprehensive formalization of statistical learning theory in Lean 4 addresses gaps in mathematical libraries and demonstrates human-AI collaboration for verified machine learning theory foundations...

🔹 Publication Date: Published on Feb 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.02285
• PDF: https://arxiv.org/pdf/2602.02285
• Github: https://github.com/YuanheZ/lean-stat-learning-theory

✨ Datasets citing this paper:
• https://huggingface.co/datasets/liminho123/lean4-stat-learning-theory-novel
• https://huggingface.co/datasets/liminho123/lean4-stat-learning-theory-random
• https://huggingface.co/datasets/liminho123/lean4-stat-learning-theory-corpus

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

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

#AI #DataScience #MachineLearning #HuggingFace #Research

✨Optimal Turkish Subword Strategies at Scale: Systematic Evaluation of Data, Vocabulary, Morphology Interplay

📝 Summary:
This study systematically evaluates Turkish subword tokenization, varying vocabulary and corpus size across multiple tokenizer families and diverse linguistic tasks. It introduces morphology-aware diagnostics to provide actionable guidance for building effective tokenizers in morphologically rich...

🔹 Publication Date: Published on Feb 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.06942
• PDF: https://arxiv.org/pdf/2602.06942

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

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

#AI #DataScience #MachineLearning #HuggingFace #Research

✨KV-CoRE: Benchmarking Data-Dependent Low-Rank Compressibility of KV-Caches in LLMs

📝 Summary:
KV-CoRE method evaluates kv-cache compressibility through SVD-based low-rank approximation, revealing patterns linking compressibility to model architecture and training data across multiple languages...

🔹 Publication Date: Published on Feb 5

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.05929
• PDF: https://arxiv.org/pdf/2602.05929

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

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

#AI #DataScience #MachineLearning #HuggingFace #Research

✨CauScale: Neural Causal Discovery at Scale

📝 Summary:
CauScale is a neural architecture that enables efficient causal discovery on large graphs through compressed embeddings and tied attention weights, achieving high accuracy and significant speedups ove...

🔹 Publication Date: Published on Feb 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.08629
• PDF: https://arxiv.org/pdf/2602.08629

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

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

#AI #DataScience #MachineLearning #HuggingFace #Research

✨f-GRPO and Beyond: Divergence-Based Reinforcement Learning Algorithms for General LLM Alignment

📝 Summary:
Preference alignment objectives are extended to general alignment settings using f-divergence variational representations, introducing novel on-policy and hybrid policy optimization methods for LLM al...

🔹 Publication Date: Published on Feb 5

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.05946
• PDF: https://arxiv.org/pdf/2602.05946

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

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

#AI #DataScience #MachineLearning #HuggingFace #Research

✨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

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

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

#AI #DataScience #MachineLearning #HuggingFace #Research

✨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

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

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

#AI #DataScience #MachineLearning #HuggingFace #Research

✨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

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

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

#AI #DataScience #MachineLearning #HuggingFace #Research

✨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

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

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

#LLM #AICopyright #AISafety #ResponsibleAI #AIResearch

✨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/

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

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

#AI #DataScience #MachineLearning #HuggingFace #Research

✨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

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

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

#AI #DataScience #MachineLearning #HuggingFace #Research

✨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

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

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

#AI #DataScience #MachineLearning #HuggingFace #Research

✨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

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

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

#AI #DataScience #MachineLearning #HuggingFace #Research

✨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

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

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

#AI #DataScience #MachineLearning #HuggingFace #Research

✨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

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

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

#AI #DataScience #MachineLearning #HuggingFace #Research

✨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

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

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

#AI #DataScience #MachineLearning #HuggingFace #Research

✨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/

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

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

#AI #DataScience #MachineLearning #HuggingFace #Research

✨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

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

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

#AI #DataScience #MachineLearning #HuggingFace #Research

✨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

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

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

#AI #DataScience #MachineLearning #HuggingFace #Research

✨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

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

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

#AI #DataScience #MachineLearning #HuggingFace #Research