Notable data and AI papers

627 papers · 45 labs

LoongRL:Reinforcement Learning for Advanced Reasoning over Long Contexts research paper by Microsoft, 2025

Microsoft · Reasoning · Oct 22, 2025 · 34 citations · 63 upvotes · unverified

Read on arXiv

What it shows

LoongRL, a data-driven reinforcement learning method, enhances long-context reasoning by transforming short multi-hop QA into high-difficulty tasks, improving accuracy and generalization in large language models.

By Siyuan Wang, Gaokai Zhang, Li Lyna Zhang and 4 more · arXiv 2510.19363 · PDF

UnverifiedHugging Face's summary; not yet checked by hand.

More from Microsoft

All 57
Agents and evaluationUnverifiedNov 2, 2026WebHarbor: Docking Real Websites for Evolving GUI Agent EnvironmentsWebHarbor provides realistic, containerized website environments for training and testing computer-using web agents across complex online tasks.Microsoft28 upvotesRead →Agents and evaluationUnverifiedOct 19, 2026Agent World Model in the Wild: Computer-Use Agent Environment SynthesisThis pipeline creates controllable, open-source environments to safely train and test AI agents on complex, long-horizon computer-use tasks.Microsoft69 upvotesRead →Training and scalingUnverifiedOct 16, 2026Self-Evolving Coding Agents via Harness-Policy OptimizationThis framework improves coding agents by recursively alternating between optimizing the agent's policy and the environment harness it uses to interact with code.Microsoft48 upvotesRead →Multimodal and roboticsUnverifiedOct 13, 2026AesCode: Aesthetic Code Generation with Decoupled Cross-Modal RewardsThis paper introduces a method to improve code-based visual generation by using image-based aesthetic guidance and decoupled rewards to ensure quality and correctness.Microsoft137 upvotesRead →Training and scalingUnverifiedOct 13, 2026APT: Feedback-Driven Agentic Post-Training for Text-to-Image GenerationThis paper introduces an automated post-training framework that uses a feedback loop of evaluation and diagnosis to improve text-to-image models.Microsoft23 upvotesRead →Multimodal and roboticsUnverifiedOct 13, 2026LensErase: A Foundation Model for Erase AnythingThis paper introduces a foundation model designed for versatile image editing and object removal using mask-based inputs and efficient positional encoding.Microsoft52 upvotesRead →Inference and efficiencyUnverifiedOct 13, 2026Simplifying and Improving On-Policy Distillation for Few-Step DiffusionThis paper introduces a simplified regression-based method for distilling diffusion models that improves generation speed without requiring complex training techniques.Microsoft27 upvotesRead →Applied AIUnverifiedOct 5, 2026MiniCorp: The Last Mile of the AI Agent FirmMiniCorp is an office simulator that allows researchers to study how agents run companies and generate enterprise data for training.Microsoft39 upvotesRead →
Topic
ReasoningJan 28, 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language ModelsAsking a model to write out its intermediate steps (chain of thought) sharply improves its math and logic answers.Google23.8k citations16 upvotesRead →ReasoningUnverifiedFeb 5, 2024DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language ModelsDeepSeekMath 7B improves mathematical reasoning through enhanced data pre-training and Group Relative Policy Optimization, achieving high scores on MATH benchmark without external tools.DeepSeek10.6k citations152 upvotesRead →ReasoningJan 22, 2025DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement LearningReinforcement learning taught a model long step-by-step reasoning on par with OpenAI o1.DeepSeek5,972 citations458 upvotesRead →ReasoningUnverifiedJun 17, 2024DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code IntelligenceDeepSeek-Coder-V2, a Mixture-of-Experts language model, excels in code-specific tasks by enhancing coding and mathematical reasoning capabilities while expanding language support and context length.DeepSeek530 citations73 upvotesRead →ReasoningUnverifiedAug 11, 2025MolmoAct: Action Reasoning Models that can Reason in SpaceAction Reasoning Models (ARMs) integrate perception, planning, and control to enable adaptable and explainable robotic behavior, achieving superior performance across various tasks and settings.Ai2232 citations45 upvotesRead →ReasoningUnverifiedJul 22, 2025ThinkAct: Vision-Language-Action Reasoning via Reinforced Visual Latent PlanningThinkAct, a dual-system framework, uses reinforced visual latent planning to enable few-shot adaptation, long-horizon planning, and self-correction in embodied AI tasks by bridging high-level reasoning with low-level action execution.NVIDIA192 citations43 upvotesRead →
About this paper
Venue
arXiv.org
Citations
34, 7 influential · Semantic Scholar
Upvotes
63 · Hugging Face
Lab
Microsoft · on Companies · on Acquisitions · on Quarterly · on Paydays · on Releases · on TechConf

Changes

CitationsNov 2, 2026Influential citations rose from 5 to 7.
CitationsNov 2, 2026Citations rose from 30 to 34.
CitationsOct 12, 2026Citations rose from 28 to 30.
CitationsOct 5, 2026Citations rose from 25 to 28.
CitationsSep 25, 2026A first count of 5 influential citations.
CitationsSep 25, 2026A first count of 25 citations.
New paperSep 25, 2026Found by the weekly Hugging Face scan; not yet checked by hand.