World in World: Explore the World with World Models
Paper • 2609.11548 • Published • 2
GuoLiangTang
Tommy930
AI & ML interests
LLM，NLP，ML
Recent Activity
upvoted a paper about 4 hours ago
World in World: Explore the World with World Models upvoted a paper about 4 hours ago
Recursive Code World Models: Building Complex Worlds through Recursive Scene Programs upvoted a paper about 4 hours ago
EvoSafeHarness: Evolving Model- and Domain-Specific Harnesses for Securing AgentsOrganizations
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upvoted 4
papers about 4 hours ago
Recursive Code World Models: Building Complex Worlds through Recursive Scene Programs
Paper • 2609.11499 • Published • 4
EvoSafeHarness: Evolving Model- and Domain-Specific Harnesses for Securing Agents
Paper • 2609.05903 • Published • 33
SenseNova-U1.5: Towards Native Unified Visual Intelligence
Paper • 2609.11929 • Published • 78
upvoted 5
papers about 5 hours ago
NCP-ArchPreview Technical Report: Moving towards Latent Space Language Models through Next Concept Prediction
Paper • 2609.10715 • Published • 99
PARSER: Read in Parallel, Reason in Depth for Long-Context LLM Agents
Paper • 2609.06702 • Published • 12
Why Is Video Still So Expensive? A Survey of Inference-Efficiency Mechanisms in Video and Audiovisual LLMs
Paper • 2609.10355 • Published • 5
T1: Terminal Agent Reinforcement Learning for Long-Horizon Tasks
Paper • 2609.11042 • Published • 34
Scaling Automatic Research Agents via World Models
Paper • 2608.12564 • Published • 432
upvoted 2
papers about 22 hours ago
upvoted 9
papers 1 day ago
WearableQA: A Benchmark for Health Reasoning over Real-World Wearable Data
Paper • 2609.05405 • Published • 31
SAEScientist-Bench: Can AI Agents Conduct Autonomous SAE Interpretability Research?
Paper • 2609.09113 • Published • 16
Co-Evolving Harnesses and Models: On-Policy Correction Helps Weaker Models Catch Up Where Imitation Fails
Paper • 2609.09134 • Published • 4
DianShi-RxnDB: A Large-Scale, Fine-Grained Organic Reaction Data Platform Built via a Fully Automated Pipeline for Researchers and AI Agents
Paper • 2609.06703 • Published • 9
Φ-Bench: Can Large Language Models Engineer the Infrastructure That Powers Them?
Paper • 2609.10226 • Published • 9
Programmable World Model
Paper • 2609.10540 • Published • 83
Show-Harness: Just a VLM Agent Can Play Robots
Paper • 2609.10522 • Published • 132
Graph Machine: Towards Better Pretraining via Edges
Paper • 2609.02881 • Published • 3
EVOHARNESSBENCH: Can Your Agents Keep Pace with an Evolving Harness?
Paper • 2609.04280 • Published • 5