논문해외HF Daily Papers
Few-Step Streaming Video Generation via Condition Shifting
Few-step sampling reduces the cost of streaming video generation. Distribution Matching Distillation (DMD) supervises few-step generators with a separate…
AI 속보
한국시간 기준 · 같은 소식은 가장 최근 보도 하나로 묶어 보여 드립니다.
2026년 11월 10일 (화)
- 논문해외HF Daily Papers
ExRL: Sample-Efficient Online Adaptation of Long-Chunk Policies via Execution Length Control
Predicting long action chunks, often spanning dozens of timesteps, has become a key ingredient in increasingly capable robot policies.
2026년 11월 9일 (월)
- 논문해외HF Daily Papers
How Many Exposures Does a World Model Need? Learning Unseen Game Mechanics at Test Time
World models enable agents to plan and learn from imagined experience, but in an unfamiliar environment they must learn its mechanics from limited interaction.
- 논문해외HF Daily Papers
Sage-Taiyi: A Metacognitive Architecture for Scientific Discovery
We introduce Sage-Taiyi, a metacognition-inspired architecture that uses accumulated scientific understanding to guide what to investigate next and how to…
- 논문해외HF Daily Papers
Learning Heterogeneous Tactile Representation for General Dexterous Manipulation
Tactile sensing is an indispensable modality for contact-rich dexterous manipulation, a capability that hints at the ultimate frontiers of embodied…
- 논문해외HF Daily Papers
Reframe: Observation-Aligned Multi-Teacher On-Policy Distillation for Agentic Visual Reasoning
Agentic reinforcement learning (RL) and multi-teacher on-policy distillation (MOPD) offer complementary routes to post-training.
- 논문해외HF Daily Papers
Training Vision Transformers to Focus: Emergence of Spatial Attention Head Specialization
Self-supervised learning in Vision Transformer models, such as DINO, enables robust visual perception without requiring labeled data by leveraging large-scale…
- 논문해외HF Daily Papers
SWAM: Scaling World Action Models with Cross-Modal Alignment
World action models jointly predict video and actions conditioned on language.
- 논문해외HF Daily Papers
Click3R: Interactive Stereo 3D Reconstruction with Sparse Correspondence Clicks
Despite impressive progress, existing feed-forward large 3D reconstruction models produce a single, irrevocable prediction.
- 논문해외HF Daily Papers
Creative Priming: Decoupling Process from Product to Escape the Creative Paradox
Many of the most consequential advances promised by AI, from curing diseases and inventing new technologies to formulating new scientific theories, are…
- 논문해외HF Daily Papers
FraudBench: A Legal Evaluation of AI Deception
We introduce FraudBench, an evaluation of large language models' (LLMs) propensities to recommend, assist, or directly take actions that would constitute fraud…
- 논문해외HF Daily Papers
Infrathon: Benchmarking Language Agents for Real-World, Long-Horizon AI Infra Optimization
In this work, we study whether frontier agent can continually improve real-world AI infrastructure over long horizons.
- 논문해외HF Daily Papers
EmoHarness: Boosting Multimodal Emotion Understanding with Meta-Harness Evolving
Small multimodal models can misjudge emotion when words, voice, and visual cues conflict.
- 논문해외HF Daily Papers
dNaViT: Discrete Codes are General-Purpose Visual Representations
Discrete autoregressive modeling, notably through next-token prediction, has become a cornerstone of modern language models.
- 논문해외HF Daily Papers
PhysOPSD: Code as Privilege for Physically Plausible Video Generation
While modern video generative models achieve remarkable visual fidelity, they remain noticeably brittle when generating physically plausible dynamics and…
- 논문해외HF Daily Papers
World In-Context Learning for Agentic Robot Manipulation
Trained action policies write manipulation skill into network weights, tying what is learned to the distribution it is learned from.
2026년 11월 8일 (일)
- 논문해외HF Daily Papers
InfraRSI: Harnessing Recursive Self-Improvement for Training Infrastructure
While Recursive Self-Improvement (RSI) accelerates isolated algorithm and kernel synthesis, distributed LLM training depends on tightly coupled launch…
- 논문해외HF Daily Papers
How Much Training-Inference Mismatch Can On-Policy Distillation Tolerate?
On-policy distillation (OPD) trains a student language model on its own responses, guided by a fixed teacher.
- 논문해외HF Daily Papers
Spatial Harness: Grounding Spatial Reasoning in Executable World States with Physics Engines
Spatial reasoning requires understanding how objects and observers are arranged in a scene and how their relations change with viewpoint or movement.
2026년 11월 7일 (토)
- 논문해외HF Daily Papers
WorldFoundry: Towards Unified Infrastructure for World Intelligence
Visual generative models increasingly blur the line between synthesizing observations and simulating environments.
같은 소식 다른 보도r/StableDiffusion - 논문해외HF Daily Papers
JoVox: Joint Hierarchical Flow Matching for Lightweight Voxel Generation
Generating high-fidelity voxels while keeping their lightweight nature remains an open problem in computer vision.
- 논문해외HF Daily Papers
Coding or Cheating? An Investigation of Frontier Coding LLMs
Frontier agentic LLMs are trained on verifiable rewards in reinforcement learning (RL) environments built from real software repositories.
- 논문해외HF Daily Papers
Horizon-Scalable Q-Learning
Learning accurate off-policy state-action value functions (Q-functions) from offline datasets becomes harder as the task horizon grows.
- 논문해외HF Daily Papers
Energy-Tweedie: Score meets Score, Energy meets Energy
Denoising and score estimation are classically linked through Tweedie's formula, which relates the posterior mean under Gaussian noise to the Stein score of…
- 논문해외HF Daily Papers
onóna: Twin Embeddings with Tied Unembeddings
Weight tying reduces the parameter cost of language models, but the usual tied output head is limited to a single softmax.
- 논문해외HF Daily Papers
MotionGraphicsBench: Evaluating Motion Graphics Generation with Programmatic Verification
Large language models can generate motion graphics from static images and natural language requests, but it remains difficult to evaluate how well models can…
- 논문해외HF Daily Papers
Predictive Surprise as Self-Grounding Concept Bottleneck for Interpretable Time Series
Time-series classifiers deployed in risk-sensitive domains must be (1) accurate, (2) interpretable, and (3) able to abstain when evidence is weak.
- 논문해외HF Daily Papers
Longtail-SWE: High-Quality SWE Tasks for Underrepresented Languages
Challenging repository-level benchmarks remain limited for many programming language ecosystems, where filtering scarce candidates with ambiguous descriptions…
2026년 11월 6일 (금)
- 논문해외HF Daily Papers
InstantHMR : Real-Time Human Mesh Recovery on Your Phone
Real-time 3D human mesh recovery from a single image on mobile devices is a challenging problem with many applications, including robotics, biomechanics…
- 논문해외HF Daily Papers
Authorization Drift in LLM Agents: Evaluating Boundary Compliance in Multi-Step Tool Use
LLM agents can exceed their authorization boundaries while pursuing user goals without an adversary.