HuggingFace
Lite Any Stereo V2: Faster and Stronger Efficient Zero-Shot Stereo Matching
Recent advances in stereo matching have achieved remarkable accuracy, but often rely on large models, heavy computati...
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HuggingFace
Speaker Identity in Non-Verbal Vocalizations: Conditional Distillation and Mixture of Experts Approach
As expressive text-to-speech (TTS) and voice conversion (VC) systems increasingly generate non-verbal vocalizations (...
HuggingFace
Plans Don't Persist: Why Context Management Is Load Bearing for LLM Agents
Long-horizon agents depend on context management: systems compress, summarize, and evict old tokens so tasks can cont...
HuggingFace
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...
HuggingFace
Do Thinking Tokens Help with Safety?
Today's reasoning models use thinking tokens to attain stronger performance on benchmarks than their instruction-tune...
HuggingFace
Physics Question Scene Graph: Fine-grained Evaluation of Physical Plausibility in Text-to-Video Generation
Video generation models are increasingly capable of producing realistic videos, but they still struggle to generate v...
arXiv
Autodata: An agentic data scientist to create high quality synthetic data
We introduce Autodata, a general method that enables AI agents to act as data scientists who build high quality train...
arXiv
Variable Bound Tightening for Nash Equilibrium Computation in Multiplayer Imperfect-Information Games
There has been significant recent progress in algorithms for approximation of Nash equilibrium in large two-player ze...
arXiv
Hierarchical Reinforcement Learning for Neural Network Compression (HiReLC): Pruning and Quantization
We present HiReLC, a hierarchical ensemble-reinforcement learning framework for automated joint quantization and stru...
arXiv
FORCE: Efficient VLA Reinforcement Fine-Tuning via Value-Calibrated Warm-up and Self-Distillation
Vision-Language-Action (VLA) models are often constrained by the imitation ceiling imposed by sub-optimal data. While...
arXiv
Privacy Vulnerabilities of Attention Layers in Tabular Foundation Models and Protection of High-Risk Queries
Tabular foundation models are commonly assumed to present limited privacy concerns as they are often pre-trained on l...
arXiv
Can Trustless Agents Be Trusted? An Empirical Study of the ERC-8004 Decentralized AI Agent Ecosystem
As autonomous AI agents increasingly transact across organizational boundaries, a fundamental trust challenge emerges...