Papersby GlyphEvery tracked research paper
VFlash: Fast, Accurate Visual Planning via Flash Primitive DecodingA method called VFlash speeds up and improves visual motion planning for robots by predicting entire spatial shapes at once.
NVIDIA109 upvotesRead →MoviEdit: Long-form Multi-Shot Video Editing Made EasyMoviEdit is a framework and benchmark for editing long videos across multiple camera shots and changing scenes.
Adobe75 upvotesRead →RoboColosseum: Evaluating Physical Intelligence at Scale In-The-WildRoboColosseum is an evaluation framework that tests robot AI models across different environments and physical setups.
Hugging Face50 upvotesRead →WebHarbor: 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 →Random Is Almost Enough? Stable and Low-Cost Benchmark Compression via BestRandBestRand is a method for selecting small benchmark subsets that reliably estimate full evaluation scores at lower computational costs.
Carnegie Mellon University51 upvotesRead →Apriel Voice 27B Preview: An Open Model for Speech, Reasoning, and Tool UseApriel Voice 27B is an open AI model that directly processes spoken speech to converse, reason, and use external tools.
ServiceNow37 upvotesRead →EmbeddingGemma 2: Unified and Efficient Multimodal RepresentationsEmbeddingGemma 2 is an open multimodal embedding model that unifies text, images, audio, and video representations with efficient resource-flexible design and state-of-the-art benchmark performance.
Google34 upvotesRead →Nemotron-Labs-Diffusion-Uni: Elastic Self-Refining Unified Diffusion LLM with Cross-Paradigm On-Policy DistillationNLD-Uni is a unified discrete diffusion language model that combines visual understanding and generation via cross-paradigm on-policy distillation and progressive self-refining diffusion.NVIDIA12 upvotesRead →ThinkWorld: World Imagination Reinforces Chain-of-Dynamics ReasoningThinkWorld improves robotic generalization by representing actions as dynamics chains and using world imagination to learn from unlabeled human videos.NVIDIA57 upvotesRead →Co-Design Bench: Multimodal Collaborative Coding Evaluation for Agentic ModelsCo-Design Bench evaluates how effectively coding agents update software applications based on user requests with text, images, and other media.
Alibaba (Qwen)23 upvotesRead →StreamVibe: Proactive Video Agents for Evolving User IntentStreamVibe introduces a benchmark, streaming vision-language model, and hierarchical memory harness to enable proactive, intent-aware interaction with implicit and evolving user goals.Google78 upvotesRead →InteractiveWorld: A Verifiable Human-Centric Environment for Building Better Interactive MLLM AssistantsInteractiveWorld provides a verifiable simulation environment and benchmark to evaluate whether multimodal language models can reliably guide humans through physical tasks.
Meta46 upvotesRead →Eat Your Precision: Precision Objective Mitigates Reward Hacking in Rubric-based RLFORK jointly optimizes recall and precision via rubric-driven necessity credits and factual grading to improve response quality and reduce verbosity in reinforcement learning.Carnegie Mellon University34 upvotesRead →Qwen-Image-PE: Learning Visual Design for Text-to-Image Prompt EnhancementQwen-Image-PE improves text-to-image prompts via two-stage training with caption-based reverse distillation and groupwise design rewards, scaling across data, model size, and information density.Alibaba (Qwen)23 upvotesRead →On-Policy Self-Training: Data-Free Self-Improvement in Large Language ModelsFoundation models can self-improve across text and vision tasks by generating synthetic questions and reasoning traces guided only by high-level topics, without external supervision.Google31 upvotesRead →OTel: Open Telco AI Datasets, Benchmarks, and ModelsOpen Telco provides open telecom AI datasets and post-trained baselines for retrieval, reranking, and instruction-tuned language models, improving benchmark performance across all three families.
AT&T1 citationsRead →World-in-Context: Interactive Video World Modeling with In-Context ConditioningWorld-in-Context unifies view, action, and camera controls via explicit tokens and interaction-aware positional encoding to improve interactive video generation and navigation.Alibaba (Qwen)22 upvotesRead →Beyond Watching and Searching: Benchmarking Agents for Video-centered Deep Research ReportsThis benchmark evaluates how well AI agents can research and synthesize information from videos to produce interactive reports.Alibaba (Qwen)19 upvotesRead →UserArena: Benchmarking Interactive User Simulation for Long-Horizon Shopping AgentsUserArena introduces a real-world interactive benchmark with long-horizon shopping trajectories and an evaluation framework, alongside On-Policy Trajectory Distillation to improve simulator fidelity for agentic recommendations.Alibaba (Qwen)55 upvotesRead →Retrieval Augmented Generation CompositionalityThis study shows that individual RAG techniques do not always work well together and provides a framework to evaluate full retrieval pipelines.
IBM34 upvotesRead →Automating ML for Science: Can Frontier Agents Climb Scientific Hills in the Wild?This testbed evaluates how well AI agents can improve scientific machine learning models and identifies their reliance on engineering tricks over research insight.
Anthropic18 upvotesRead →Joints, Camera, Action! Co-Generating 3D Motion and Video for Arbitrary RigsThis model generates both video and 3D motion for any character rig, allowing the motion to be replayed accurately within a 3D scene.NVIDIA26 upvotesRead →Agent 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 →OpenVLHarness: Real World Visual Agentic Tool-Use with Multimodal MemoryThis framework improves multimodal AI reasoning by providing persistent memory and tool interfaces to help models process and combine complex visual evidence.
Apple101 upvotesRead →SWIFT: Self-guided Weak-to-strong dIFfusion models via Target extrapolationThis training method uses a smaller, frozen model to guide the training of a larger diffusion model, improving quality without increasing inference costs.Alibaba (Qwen)30 upvotesRead →Self-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 →BlenderWorld: Benchmarking Visual Agents for 3D Creation from Real-World ReferencesThis benchmark evaluates how well AI models can perform complex 3D creation and editing tasks within the Blender software.Alibaba (Qwen)23 upvotesRead →CommerceGen-Studio: An End-to-End Framework for Commercial-Grade Main-Image GenerationThis paper presents an end-to-end framework for generating commercial-grade e-commerce product images by combining metadata extraction, layout planning, and multi-condition generation.Alibaba (Qwen)25 upvotesRead →Correction Training for Diffusion ModelsThis method adds a correction step to diffusion models to fix errors that accumulate during the image generation process.
UC Berkeley42 upvotesRead →DeLoop: Repeated Actions as Self-Supervision for Long-Horizon AgentsThis self-supervised training method teaches AI agents to avoid repetitive, unproductive actions during long tasks by using their own history as feedback.Google21 upvotesRead →AesCode: 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 →APT: 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 →CLASHarness: Benchmarking Multi-Agent Conflict in Computer Use via a Controllable and Verifiable Generation PipelineThis paper introduces a benchmark and generation pipeline to evaluate how agents resolve conflicts and verify information in multi-agent computer-use scenarios.Google36 upvotesRead →EdgeWise: Bringing Long-Horizon Agents to the Edge via Selective Cloud DelegationThis paper introduces a framework that reduces inference costs by using a small local model for most tasks and delegating only critical steps to the cloud.NVIDIA30 upvotesRead →Fish Audio Drama 3 Technical ReportThis paper introduces an open-source speech generation model capable of multi-turn performance, character-specific voice cloning, and real-time audio editing.
Fish Audio26 upvotesRead →FlashMask-3: Efficient and Expressive Mask-Aware Distributed AttentionFlashMask-3 accelerates long-context attention via a Hopper-optimized sparse-mask kernel and distributed context-parallel extensions that eliminate mask-communication overhead and improve training throughput.
Baidu11 upvotesRead →Hybrid Reasoning AgentsThis paper introduces an agent architecture that dynamically switches between latent reasoning and text-based interaction to improve performance and inference speed.
Stanford University41 upvotesRead →Into the Unknown: Benchmarking AI agents on open scientific research problemsThis benchmark evaluates how well AI agents can write follow-up scientific research papers based on unpublished directions from domain experts.Carnegie Mellon University62 upvotesRead →LensErase: 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 →Simplifying 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 →Urbex: Agentic Spatial Grounding for City-Scale 3D ScenesThis paper presents an agentic framework that treats city-scale 3D scene grounding as an active search task rather than a simple candidate ranking problem.Alibaba (Qwen)134 upvotesRead →Virtual Head AttentionVirtual Head Attention improves long-context model efficiency by reducing KV cache and compute while preserving quality through lightweight linear query and output transformations.Baidu17 upvotesRead →X-Ragent: Tool-Augmented Reinforcement Learning for Evidence-Grounded Chest X-Ray ReasoningThis paper introduces a reinforcement learning framework for medical agents that selectively uses external evidence to improve diagnostic reasoning in chest X-rays.Carnegie Mellon University44 upvotesRead →Last Secure Code Benchmark: Is the Code You Vibe Secure?This paper introduces a benchmark showing that current coding agents frequently produce functional but insecure code, highlighting significant security risks in automated coding.Alibaba (Qwen)77 upvotesRead →Harness^2: Recursive Agent Harnessing for an Open WorldThis paper introduces a recursive framework that allows agents to automatically improve their own execution harnesses for better performance on novel open-world tasks.Google2 citations123 upvotesRead →Learning Representations to Guide Pixel Diffusion TransformersThis paper introduces a guidance method for diffusion transformers that uses compact internal representations to improve image generation quality and efficiency.Alibaba (Qwen)34 upvotesRead →Scaling Agentic Data for Long-Horizon Terminal IntelligenceThis paper introduces a system to automatically generate high-quality training data for long-horizon terminal agents to improve their autonomous problem-solving capabilities.Alibaba (Qwen)1 citations147 upvotesRead →Thinking Inertia: LLMs Keep Thinking When Told Not ToThis paper shows that explicit controls often fail to stop LLMs from generating internal reasoning traces, a phenomenon the authors call thinking inertia.Stanford University244 upvotesRead →When Do We Need On-Policy Distillation? Distilling on Offline Student Rollouts Is Often BetterThis paper shows that distilling from offline student rollouts is often more efficient and accurate than standard on-policy distillation for many model pairs.NVIDIA28 upvotesRead →Long-WAM: Scaling the Context of World-Action ModelsLong-WAM improves robot control by using autoregressive pretraining to effectively leverage long visual histories for real-time action prediction.NVIDIA2 citations114 upvotesRead →