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Decompile-Bench: The First Million-Scale Real-World Benchmark for Training and Evaluating LLM-Powered Binary Decompilers

Decompile-Bench: The First Million-Scale Real-World Benchmark for Training and Evaluating LLM-Powered Binary Decompilers 6178

Decompiling machine code back into human-readable source remains one of the most challenging and valuable tasks in software engineering, cybersecurity,…

12/19/2025Binary Decompilation, Code Translation, Reverse Engineering
MiniMax-M1: The First Open-Weight Hybrid-Attention Model for Long-Context Reasoning and Efficient AI Agents

MiniMax-M1: The First Open-Weight Hybrid-Attention Model for Long-Context Reasoning and Efficient AI Agents 3001

MiniMax-M1 is a breakthrough in open large language models: it’s the world’s first open-weight, large-scale hybrid-attention reasoning model. Designed for…

12/19/2025Agentic Tool Use, Long-context Reasoning, Software Engineering Agents
Hunyuan3D 2.1: Open-Source, High-Fidelity 3D Generation from Images with Production-Ready PBR Materials

Hunyuan3D 2.1: Open-Source, High-Fidelity 3D Generation from Images with Production-Ready PBR Materials 2498

Creating high-quality 3D assets has long been a bottleneck in industries like gaming, virtual reality, industrial design, and digital content…

12/19/20253D Generation, Image-to-3D, PBR Material Synthesis
Reasoning Gym: Train and Evaluate Reasoning Models with Infinite, Verifiable Reinforcement Learning Environments

Reasoning Gym: Train and Evaluate Reasoning Models with Infinite, Verifiable Reinforcement Learning Environments 1265

If you’re building or evaluating reasoning-capable AI systems—especially large language models (LLMs)—you’ve likely hit a wall with static benchmarks. Traditional…

12/19/2025Procedural Task Generation, Reasoning, Reinforcement Learning
SageAttention3: 5x Faster LLM Inference on Blackwell GPUs with Plug-and-Play FP4 Attention and First-Ever 8-Bit Training Support

SageAttention3: 5x Faster LLM Inference on Blackwell GPUs with Plug-and-Play FP4 Attention and First-Ever 8-Bit Training Support 2814

Attention mechanisms lie at the heart of modern large language models (LLMs) and multimodal architectures—but their quadratic computational complexity remains…

12/19/2025Efficient Training, Large Language Model Inference, Multimodal Generation
Meta-World+: A Reproducible, Standardized Benchmark for Multi-Task and Meta Reinforcement Learning in Robotic Control

Meta-World+: A Reproducible, Standardized Benchmark for Multi-Task and Meta Reinforcement Learning in Robotic Control 1659

Evaluating reinforcement learning (RL) agents—especially those designed for multi-task or meta-learning scenarios—requires benchmarks that are consistent, well-documented, and technically accessible.…

12/19/2025Meta-reinforcement Learning, Multi-task Reinforcement Learning, Robotic Manipulation
SoundMind: Boost Audio-Language Models with Reinforcement-Learned Logical Reasoning

SoundMind: Boost Audio-Language Models with Reinforcement-Learned Logical Reasoning 1101

Most large language models (LLMs) today excel at reasoning over text—but what happens when the input includes sounds? Can an…

12/19/2025Audio-language Reasoning, Logical Reasoning In AI, Multimodal Reinforcement Learning
AReaL: Accelerate Language Reasoning Training with Fully Asynchronous Reinforcement Learning

AReaL: Accelerate Language Reasoning Training with Fully Asynchronous Reinforcement Learning 3143

If you’re building or fine-tuning large language models (LLMs) for reasoning—whether in math, coding, search, or agentic workflows—you’ve likely hit…

12/19/2025Agentic AI Training, Asynchronous RL, Reinforcement Learning For Reasoning
VSA: Accelerate Video Diffusion Models by 2.5× with Trainable Sparse Attention—No Quality Tradeoff

VSA: Accelerate Video Diffusion Models by 2.5× with Trainable Sparse Attention—No Quality Tradeoff 2780

Video generation using diffusion transformers (DiTs) is rapidly advancing—but at a steep computational cost. Full 3D attention in these models…

12/19/2025Diffusion Models, Sparse Attention, Video Generation
RAGEN: Train LLM Agents That Reason and Act Across Multi-Turn, Stochastic Environments

RAGEN: Train LLM Agents That Reason and Act Across Multi-Turn, Stochastic Environments 2438

Building autonomous agents that can reason, act, and adapt over multiple interaction steps remains one of the toughest challenges in…

12/19/2025LLM Agent Training, Multi-turn Reinforcement Learning, Trajectory-level Policy Optimization

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