Next Forcing: Causal World Modeling with Multi-Chunk Prediction
Autoregressive video generation has emerged as a powerful paradigm for World Action Models (WAMs). However, existing approaches suffer from slow training convergence and limited co...
Research Papers
Latest AI/ML research from ArXiv and Papers with Code
N-GRPO: Embedding-Level Neighbor Mixing for Enhanced Policy Optimization
The success of Large Language Models in mathematical reasoning relies heavily on the generation of diverse and valid solution paths during the rollout phase. However, current rollo...
WebChallenger: A Reliable and Efficient Generalist Web Agent
Autonomous web navigation remains challenging for LLM agents, and the strongest generalist systems rely on proprietary reasoning models whose inference cost is prohibitive for the ...
The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment
As AI systems built from multiple language-model agents become more common, they are increasingly used to make decisions together: discussing, negotiating, and acting on shared tas...
Flow-DPPO: Divergence Proximal Policy Optimization for Flow Matching Models
Recent work has demonstrated that online reinforcement learning (RL) can substantially improve the quality and alignment of flow matching models for image and video generation. Met...
Data Journalist Agent: Transforming Data into Verifiable Multimodal Stories
Data tells stories that shape society; the data journalist's job is to turn raw information into stories non-experts can trust. A high-quality news feature takes a newsroom team we...
WorldOlympiad: Can Your World Model Survive a Triathlon?
We introduce WorldOlympiad, a benchmark for diagnosing video-based world models across physical faithfulness, geometric consistency, and interaction fidelity. While existing benchm...
Attention Amnesia in Hybrid LLMs: When CoT Fine-Tuning Breaks Long-Range Recall, and How to Fix It
Chain-of-thought (CoT) supervised fine-tuning (SFT) is widely adopted to improve reasoning ability, yet we find that it systematically degrades long-context recall in hybrid linear...
ARM: An AutoRegressive Large Multimodal Model with Unified Discrete Representations
This paper introduces ARM, a discrete representation-based AutoRegressive Model that unifies image understanding, generation, and editing within a next-token prediction framework. ...
Dynamic Linear Attention
The scalability of Large Language Models (LLMs) to long contexts is fundamentally constrained by the quadratic complexity of standard attention, motivating the adoption of linear a...
SCAIL-2: Unifying Controlled Character Animation with End-to-end In-Context Conditioning
Controlled character animation requires transferring motion from a driving sequence to a reference character. Prior works heavily rely on intermediate representations, including po...
Workflow-GYM: Towards Long-Horizon Evaluation of Computer-use Agentic tasks in Real-World Professional Fields
Recent years have witnessed the rapid evolution of AI agents toward handling increasingly complex, real-world tasks. However, existing benchmarks rarely evaluate whether agents can...
Test-Time Gradient Guidance of Flow Policies in Reinforcement Learning
Expressive continuous control policies, such as diffusion and flow models, form the backbone of recent advances in scaling imitation learning for simulated and real robot control. ...
Decentralized Multi-Agent Systems with Shared Context
Multi-agent systems (MAS) can scale large language model reasoning at test time by decomposing complex problems into parallel subtasks. However, most existing MAS rely on centraliz...
Kwai Keye-VL-2.0 Technical Report
We introduce Kwai Keye-VL-2.0-30B-A3B, an open-source Mixture-of-Experts (MoE) multimodal foundation model designed to advance long-video understanding and agentic intelligence. To...
The Role of Feedback Alignment in Self-Distillation
Conditioning a language model on additional context, such as feedback on a previous attempt, typically improves its response. Self-distillation trains the model to retain this impr...
Embodied-R1.5: Evolving Physical Intelligence via Embodied Foundation Models
We introduce Embodied-R1.5, a unified Embodied Foundation Model (EFM) that integrates comprehensive embodied reasoning capabilities, spanning embodied cognition, task planning, cor...
i1: A Simple and Fully Open Recipe for Strong Text-to-Image Models
Diffusion models have consistently driven progress in text-to-image generation. However, it is challenging to attribute recent progress to specific modeling and data choices: state...
IDEAL: In-DEpth ALignment Makes A Discrete Representation AutoEncoder
Built on pretrained vision foundation models (VFMs), representation autoencoders (RAEs) have recently emerged as a promising approach for constructing semantically rich latent spac...
DeNovoSWE: Scaling Long-Horizon Environments for Generating Entire Repositories from Scratch
As the capabilities of LLM-based code agents continue to advance, their expected role is expanding beyond localized bug fixing in existing codebases toward architecting and impleme...
Forecasting Future Behavior as a Learning Task
Trust in an AI system is often anchored by explanations of how it works, which one then uses to forecast its behavior on new inputs. For large reasoning models (LRMs), this convent...
FadeMem: Distance-Aware Memory Consolidation for Autoregressive Video Diffusion
Autoregressive video generators synthesize long videos by generating successive temporal segments, but their historical KV cache grows with video length. Existing bounded-cache met...
P3D-Bench: Benchmarking MLLMs for Parametric 3D Generation and Structural Reasoning
Multimodal large language models can write code to produce complex programs as well as use programs to do 3D modeling, which opens up a new avenue for 3D generation powered by thei...
Beyond Uniform Token-Level Trust Region in LLM Reinforcement Learning
Reinforcement learning with verifiable rewards (RLVR) has become standard for improving LLM reasoning. However, existing PPO-style trust-region mechanisms remain position-agnostic ...