Search: “routing”

arXiv:2610.02224v1 Announce Type: new Abstract: Rapid and reliable identification of pharmaceutical residues is important for safeguarding public health, ensuring food safety, and enabling practical R

arXiv:2610.03414v1 Announce Type: cross Abstract: Consistency models (CMs) have become a leading approach for generating high-quality samples in few steps. However, adding steps can improve or degrade

Jacob Coxon @hilbertspaess and @DKokotajlo next at the NYC City Council meeting, hosted by @SpeakerMenin. Coxon cpens with “We do not know how to control any AI system yet”, which, importantly, isn’t

arXiv:2610.02300v1 Announce Type: new Abstract: Training-free safeguards for text-to-image generation often rely on a reusable safety signal, such as an unsafe direction or global toxic subspace, appl

arXiv:2610.03161v1 Announce Type: cross Abstract: Feature selection for imbalanced classification tasks such as credit card fraud and consumer default detection requires balancing predictive relevance

arXiv:2610.02381v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student on the responses it generates. Existing LLM multi-teacher OPD transfers what specialists predict through t

arXiv:2610.03454v1 Announce Type: cross Abstract: Recent progress in multimodal, high-dimensional learning has enabled foundation models to process heterogeneous, large-scale data. However, at test ti

arXiv:2610.03316v1 Announce Type: new Abstract: Designing effective heuristics for diverse combinatorial optimization problems requires substantial expertise and repeated search. Large language models

OCR is dead 🪦 Long live agentic OCR! Traditional OCR makes one pass and hands back whatever text it got. Tables get flattened, charts disappear, and multi-column layouts come out scrambled. Nothing ch

arXiv:2610.02388v1 Announce Type: new Abstract: Existing 3D large language models (LLMs) compromise on two fronts: they compress shapes into latent codebook indices or coordinate text, which removes s

arXiv:2610.02717v1 Announce Type: new Abstract: A key challenge in bringing embodied intelligence into the real world is transferring capabilities from simulation to reality and enabling agents to con

arXiv:2610.02784v1 Announce Type: new Abstract: Tactile sensing provides essential contact information for robotic manipulation, yet incorporating it into pretrained vision-language-action (VLA) model

So much reporting on the Claude or OpenAI usage of the same handful of technology companies with competing products & huge cloud infrastructure of their own. There are many, many more firms out there

arXiv:2610.03195v1 Announce Type: new Abstract: As LLM agents decide on users' behalf which product to buy, which hotel to book, or which paper to cite, a preference for items from certain sources (th

arXiv:2610.03265v1 Announce Type: cross Abstract: Large-scale pre-training has improved the generalization of neural operators across diverse PDEs. However, existing PDE foundation models still strugg

arXiv:2610.02819v1 Announce Type: new Abstract: Improving joint audio-visual reasoning in Omni Large Language Models typically incurs substantial data construction and training costs. Our diagnostics

arXiv:2610.02417v1 Announce Type: new Abstract: Advances in experimental instrumentation and automation generate increasingly rich datasets, but turning experimental observations into microscopic unde

Overview llama.cpp v0.6.0 introduces the new llama_batch_ext extended batch API (with llama_process) for mixed token/embedding inputs and MTP/deepstack state embeddings, adds support for the GLM-5.3-F

arXiv:2610.03036v1 Announce Type: cross Abstract: We present WebFovea, a vision-based web agent that placed 2nd in the WebRetriever Challenge 2026 with a final score of 57.0 out of 100. The challenge

arXiv:2610.03713v1 Announce Type: cross Abstract: Continual learning treats degradation on previously seen data as evidence of failure, a convention inherited from settings with a stationary predictio

arXiv:2610.03465v1 Announce Type: cross Abstract: K-fold cross-validation (CV) is widely used as evidence of out-of-sample performance, although folds are neither independent experiments nor equally i

arXiv:2610.02636v1 Announce Type: cross Abstract: Quantum Fourier sampling may help audit the spectral learnability of delay-based physical unclonable functions (PUFs). We ask whether that promise sur

arXiv:2610.02508v1 Announce Type: new Abstract: World action models (WAMs) have emerged as a promising paradigm for robotic control by jointly predicting future visual dynamics and actions from an ini

How is JEV any different from using an embeddings model? I really will appreciate if someone can explain this to me - because I have yet to see the difference. I'll even give you my JEV server for fre

Auto-generated synthesis of 21430 entries about arxiv-cs-lg

we're seeing our coding agent costs decrease significantly for second month in row longer blog on this later, but three quick steps we took 1/ cost visibility. you cant control what you cant measure.

Meeting notes are one of the last parts of my workflow that still depend heavily on cloud tools. I've used Fathom and lately Bluedot. Bluedot works well for me because there's no meeting bot and I get

Hey everyone, I’ve been working on a game called Anyworld. It’s a browser-based multiplayer (single player also supported) text adventure inspired by the early days of AI Dungeon, especially its brows

arXiv:2610.01618v1 Announce Type: new Abstract: Agent evaluations increasingly go beyond a single success rate, reporting metrics such as cost, consistency, and robustness. Yet they typically treat th

Clef Decision Models are now on @ollama introducing 𝚌𝚕𝚎𝚏: our first models trained by @cloudflare's workers ai team. today, we're releasing two fast and accurate decision models that top the benchmark

arXiv:2610.01397v1 Announce Type: new Abstract: Dynamic humanoid motions such as flips risk hardware damage due to suboptimal policies, disturbances or sim-to-real gaps. A motion tracking policy offer

arXiv:2610.01124v1 Announce Type: new Abstract: Electroencephalography (EEG) foundation models are often pretrained with a fixed channel vocabulary or a limited set of montages, making transfer diffic

arXiv:2610.01921v1 Announce Type: cross Abstract: Cross-lingual contrastive learning has been a core component of multilingual encoder training, but the ability to explicitly align representations is

arXiv:2610.00208v1 Announce Type: cross Abstract: This paper studies decentralized safe path following for multiple quadrotors on intersecting paths, where safety requires both collision avoidance and

arXiv:2610.01751v1 Announce Type: new Abstract: Adaptive model search is path dependent: once a challenger is adopted, it becomes the reference from which later candidates are generated. A statistical

arXiv:2610.00383v1 Announce Type: new Abstract: Modern text-to-image (T2I) systems can be improved without modifying generator parameters by adapting the external system around frozen generators. Howe

arXiv:2511.06311v2 Announce Type: replace Abstract: We present a tactile sensing method enabled by the mechanical compliance of soft robots; an externally attachable photoreflective module reads surfa

arXiv:2610.01882v1 Announce Type: cross Abstract: Multi-agent reinforcement learning (MARL) provides a powerful framework for learning coordinated behaviors through interactions with the environment.

arXiv:2610.00053v1 Announce Type: new Abstract: Four-bit floating-point (FP4) Tensor Cores accelerate matrix multiplication, but scale computation, operand packing, layout construction, and saved back

arXiv:2610.00978v1 Announce Type: cross Abstract: Time-series anomaly detection (TSAD) is difficult to generalize across datasets because heterogeneous temporal dynamics imply different notions of nor

arXiv:2610.02110v1 Announce Type: new Abstract: Transparent and specular surfaces pose a serious challenge to LiDAR-based SLAM and navigation because laser returns may pass through glass, leaving coll

arXiv:2610.01223v1 Announce Type: cross Abstract: Time-series anomaly detection trades off predictive accuracy, computational efficiency, and interpretability. We use a large language model not as the

arXiv:2610.01230v1 Announce Type: new Abstract: Efficient long-context inference is essential for large language models (LLMs), yet it poses a severe computational bottleneck. Hash-based retrieval off

arXiv:2610.02074v1 Announce Type: new Abstract: Privacy-preserving machine learning presents significant deployment challenges on the cloud for intelligent systems with confidential data. Fully Homomo

arXiv:2610.01231v1 Announce Type: cross Abstract: Generative artificial intelligence has reduced the cost of producing plausible symbolic artefacts, leading recent organisation scholarship to identify

arXiv:2610.01373v1 Announce Type: new Abstract: World models allow agents to plan in latent space by choosing a sequence of actions that most reduces the distance to a given goal state. Thus, planning