Leaderboards, eval harnesses and ablations — the contested business of deciding which model is actually better.
arXiv:2605.10822v2 Announce Type: replace Abstract: Cyber-physical system (CPS) forecasting models depend on sensor streams with noisy, biased, missing, or temporally misaligned readings, yet standar...
arXiv:2606.23496v2 Announce Type: replace Abstract: Discrete text-trigger optimization -- searching for text sequences that, when ingested by a model, steer it toward a specified objective -- underpi...
arXiv:2610.38970v2 Announce Type: replace Abstract: Current and emerging mobile networks face increasing privacy, scalability, and performance challenges as distributed learning becomes essential for...
arXiv:2611.04667v2 Announce Type: replace Abstract: Federated Learning (FL) enables collaborative training of machine learning models across distributed clients while preserving data privacy. In prac...
arXiv:2107.12636v5 Announce Type: replace-cross Abstract: Detection transformers have recently shown promising object detection results and attracted increasing attention. However, how to develop eff...
arXiv:2511.06774v2 Announce Type: replace-cross Abstract: Bilevel optimization is a central tool in computational imaging for high-dimensional hyperparameter tuning; prominent applications include le...
arXiv:2605.21139v4 Announce Type: replace-cross Abstract: Current end-to-end autonomous driving models are fundamentally constrained by the behavioral cloning ceiling of imitation learning. While rei...
arXiv:2610.04044v3 Announce Type: replace-cross Abstract: The quadratic attention cost of Vision Transformers (ViTs) forces a trade-off between spatial resolution and rollout horizon, particularly fo...
arXiv:2610.17154v2 Announce Type: replace-cross Abstract: Decoding visual stimuli from the spiking activity of retinal ganglion cells (RGCs) informs both our understanding of the retinal code and the...
arXiv:2610.23975v2 Announce Type: replace-cross Abstract: Long video understanding requires VideoLLMs to answer queries about videos spanning tens of minutes to hours, but such long videos produce fa...
arXiv:2611.03699v2 Announce Type: replace-cross Abstract: Locating competing reaction pathways is difficult when potential-energy gradients are unavailable. Here we present tReax_expedition, an energ...
arXiv:2611.05386v1 Announce Type: new Abstract: Small Language Models (SLMs) are increasingly deployed on consumer-grade hardware, yet their ability to preserve information across progressively longe...
arXiv:2611.05803v1 Announce Type: new Abstract: How much phonological knowledge do language models (LMs) possess about Chinese characters, and how is this knowledge represented and used? We introduce...
arXiv:2611.05877v1 Announce Type: new Abstract: Confidence estimates guide human review in LLM-built knowledge graphs, but better error prediction can yield little improvement in an audit. We study t...
arXiv:2611.06065v1 Announce Type: new Abstract: In natural human-AI dialogue, users' corrections, requests, and self-descriptions carry reusable signals about how they want work to be done. These sig...
arXiv:2611.06403v1 Announce Type: new Abstract: Achieving both high pronunciation accuracy and fine-grained controllability remains a central challenge in Japanese text-to-speech (TTS), as Japanese i...
arXiv:2611.06496v1 Announce Type: new Abstract: Most speech large language models (SLMs) still process speech in an offline manner. They only start responding after they receive the complete speech s...
arXiv:2611.06501v1 Announce Type: new Abstract: Simultaneous Speech Translation (SimulST) requires balancing translation quality and latency. While Large Language Models (LLMs) excel in offline trans...
arXiv:2611.06839v1 Announce Type: new Abstract: Large language model (LLM) assistants increasingly help users with everyday activities that involve time-dependent constraints. However, users may not...
arXiv:2611.06876v1 Announce Type: new Abstract: LLM agents use context compaction to manage growing interaction histories, but summarizing long histories with large models can introduce substantial d...