HuggingFace
WARP: Weight-Space Analysis for Recovering Training Data Portfolios
Foundation models are routinely released to the public, yet the data recipes used to train them -- such as domain mix...
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HuggingFace
Parameter-Efficient Quantum-Inspired Fast Weight Programmers for Traffic-Matrix Forecasting
Traffic matrices (TMs) capture network-wide origin-destination demand and are central to traffic engineering, yet acc...
HuggingFace
Scaling Laws for Grid-Based Approximate Nearest Neighbor Search in High Dimensions
Grid-based approaches to approximate nearest neighbor (ANN) search have been absent from modern scaling analyses. We ...
arXiv
OrbitQuant: Data-Agnostic Quantization for Image and Video Diffusion Transformers
Diffusion transformers (DiTs) achieve state-of-the-art image and video generation, but their multi-step sampling and ...
arXiv
Learning to Move Before Learning to Do: Task-Agnostic pretraining for VLAs
Vision-Language-Action (VLA) models are fundamentally bottlenecked by the scarcity of expert demonstrations -- triple...
arXiv
Human Capital, Not Model Benchmarks, Predicts Hybrid Intelligence in Forecasting
Whether pairing people with AI helps or hurts is usually reported as a single average effect. Using a real-money pred...
arXiv
TestEvo-Bench: An Executable and Live Benchmark for Test and Code Co-Evolution
Software tests and code evolve together: a code change should be followed by new or updated tests that record the new...
arXiv
Combating Textual Noise and Redundancy: Entropy-Aware Dense Visual Token Pruning
Visual token pruning is a crucial strategy for accelerating VLMs by compressing redundant image patches, yet existing...
arXiv
G-RRM: Guiding Symbolic Solvers with Recurrent Reasoning Models
In this work, we focus on SE-RRMs, a symbol-equivariant instantiation of RRMs that exhibits improved extrapolation to...
arXiv
Beyond Adam: SOAP and Muon for Faster, Label-Efficient Training of Machine Learning Interatomic Potentials
Machine learning interatomic potentials (MLIPs) have become a hallmark of AI for scientific simulation. While efforts...
arXiv
DemoPSD: Disagreement-Modulated Policy Self-Distillation
On-policy self-distillation (OPSD) has emerged as a practical method for training large language models (LLMs) to rea...
arXiv
Reasoning LLM Improves Speaker Recognition in Long-form TV Dramas
Long-form TV dramas present a formidable challenge for comprehensive video understanding, where deciphering complex s...