Multimodal Prompt Optimization: Why Not Leverage Multiple Modalities for MLLMs Paper • 2510.09201 • Published Oct 10 • 48
TAG:Tangential Amplifying Guidance for Hallucination-Resistant Diffusion Sampling Paper • 2510.04533 • Published Oct 6 • 47
When Thoughts Meet Facts: Reusable Reasoning for Long-Context LMs Paper • 2510.07499 • Published Oct 8 • 48
Rethinking Reward Models for Multi-Domain Test-Time Scaling Paper • 2510.00492 • Published Oct 1 • 27
ACON: Optimizing Context Compression for Long-horizon LLM Agents Paper • 2510.00615 • Published Oct 1 • 32
FLOAT: Generative Motion Latent Flow Matching for Audio-driven Talking Portrait Paper • 2412.01064 • Published Dec 2, 2024 • 47
Frame Guidance: Training-Free Guidance for Frame-Level Control in Video Diffusion Models Paper • 2506.07177 • Published Jun 8 • 23
Distilling LLM Agent into Small Models with Retrieval and Code Tools Paper • 2505.17612 • Published May 23 • 81
FedSVD: Adaptive Orthogonalization for Private Federated Learning with LoRA Paper • 2505.12805 • Published May 19 • 22
Delta Attention: Fast and Accurate Sparse Attention Inference by Delta Correction Paper • 2505.11254 • Published May 16 • 48
AdaptCLIP: Adapting CLIP for Universal Visual Anomaly Detection Paper • 2505.09926 • Published May 15 • 6
MetaUAS: Universal Anomaly Segmentation with One-Prompt Meta-Learning Paper • 2505.09265 • Published May 14 • 5
Learning to Detect Multi-class Anomalies with Just One Normal Image Prompt Paper • 2505.09264 • Published May 14 • 5
Few-Shot Anomaly-Driven Generation for Anomaly Classification and Segmentation Paper • 2505.09263 • Published May 14 • 4
AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challenge Paper • 2505.10468 • Published May 15 • 9
Real2Render2Real: Scaling Robot Data Without Dynamics Simulation or Robot Hardware Paper • 2505.09601 • Published May 14 • 6
The CoT Encyclopedia: Analyzing, Predicting, and Controlling how a Reasoning Model will Think Paper • 2505.10185 • Published May 15 • 26
T1: Tool-integrated Self-verification for Test-time Compute Scaling in Small Language Models Paper • 2504.04718 • Published Apr 7 • 42