Search: “inference”

SATOR: Backpropagation-Free 3D Test-Time Adaptation via Sample-Adaptive Token Routing

arXiv:2610.21367v1 Announce Type: new Abstract: Test-time adaptation (TTA) mitigates the performance degradation of source-pretrained models on unlabeled test data under distribution shifts. Recent ba

researcharxiv-cs-cv

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Score Mismatch and Set-Constrained Sampling in Zero-Shot Conditional Discrete Diffusion

DGX agent

arXiv:2610.21061v1 Announce Type: cross Abstract: Discrete diffusion models have become a powerful framework for modeling complex discrete distributions across a range of applications. While theoretic

safetyarxiv-cs-lg

16 Oct 2026

Self-Refining Vision Language Model for Robotic Failure Detection and Reasoning

arXiv:2602.12405v2 Announce Type: replace-cross Abstract: Reasoning about failures is crucial for building reliable and trustworthy robotic systems. Prior approaches either treat failure reasoning as

applicationsarxiv-cs-lg

Skill-Decoupled On-Policy Expert Distillation for Unified Vision-Language Models

arXiv:2610.22217v1 Announce Type: cross Abstract: Reinforcement learning (RL) can elicit specialized visual capabilities in vision-language models (VLMs), yet jointly optimizing heterogeneous objectiv

safetyarxiv-cs-ai

Spark-0: Scaling Spatially Aligned Tactile Pretraining for Robot Dexterous Manipulation

model-releasesarxiv-cs-ro

arXiv:2610.22342v1 Announce Type: new Abstract: Generalist robot policies benefit from large-scale visual pretraining but often struggle with contact-rich dexterous manipulation, where force, complian

SPEAR: Selective Preference Elicitation with Adaptive Rewards for VLM-Guided Robotic Manipulation

arXiv:2610.21621v1 Announce Type: new Abstract: Recent Vision-Language Models (VLMs) enable automated preference labeling for robotic manipulation, yet their deployment remains impractical since each

applicationsarxiv-cs-ro

SSR: Structural Signal Retriever for Scalable Agent Discovery in LLM-Orchestrated Multi-Agent Systems

arXiv:2610.21113v1 Announce Type: cross Abstract: Large-scale multi-agent ecosystems require mechanisms for discovering suitable agents without exposing entire registries to a large language model (LL

Stochastic Gradient Descent: A Nonlinear Time Series Perspective

arXiv:2610.20894v1 Announce Type: cross Abstract: This paper investigates the statistical behavior of Stochastic Gradient Descent (SGD) with constant step size under the framework of iterated random f

safetyarxiv-cs-lg

StochLOB: Heavy-Tailed Score Matching for Robust Limit Order Book Trend Prediction

arXiv:2610.21081v1 Announce Type: new Abstract: Score-based diffusion methods usually perturb data with Brownian Gaussian noise, corresponding to a light-tailed forward stochastic differential equatio

Temporal Specification Guidance for Text-to-Video Generation

arXiv:2610.20822v1 Announce Type: new Abstract: Text-to-video models often generate the visual concepts requested in natural language prompts but fail to satisfy their intended ordering, timing, and p

The World Won't Wait: Evaluating and Teaching Agents Under a Live Clock

arXiv:2610.20665v1 Announce Type: new Abstract: Large language model (LLM) agents can solve complex interactive tasks, yet reasoning and tool calls take time. In continuously changing environments, an

Thinking-Free Policy Initialization Makes Distilled Reasoning Models More Effective and Efficient Reasoners

arXiv:2509.26226v3 Announce Type: replace-cross Abstract: Reinforcement Learning with Verifiable Reward (RLVR) effectively solves complex tasks but demands extremely long context lengths during traini

safetyarxiv-cs-cl

UniFGVC: Universal Training-Free Few-Shot Fine-Grained Vision Classification via Attribute-Aware Multimodal Retrieval

arXiv:2508.04136v4 Announce Type: replace-cross Abstract: Few-shot fine-grained visual classification (FGVC) aims to discriminate between subtly different categories with very limited data. While Mult

When Reality Outpaces Cognition: A New Scaling Principle for Reliable Intelligence

arXiv:2610.20764v1 Announce Type: new Abstract: This paper challenges the understanding capabilities of existing AI paradigms and emerging world models by asking a fundamental question: How quickly ca

Witness Overlap: Directional Provenance Inside Open-Weight Model Families

arXiv:2609.31784v2 Announce Type: replace Abstract: Open-weight models are often released, fine-tuned, aligned, merged, and re-released, making provenance audits ask not only whether checkpoints are r

Local Ai

Wolof-Adapted Industry-Ready Open-Weight Language Models

arXiv:2610.20824v1 Announce Type: cross Abstract: Wolof is spoken by 23M people, mostly in Senegal, but remains weakly supported by open-weight language models, while API models raise cost, governance

local-aiarxiv-cs-ai

X-Fly: Learning to Reach and Stop in Full-Chunk Aerial Vision-Language Navigation

arXiv:2610.21450v1 Announce Type: cross Abstract: Aerial vision-language navigation (VLN) agents built on large vision-language models are expensive to query. Executing a complete predicted action chu

safetyarxiv-cs-ai

A Counterfactual Graph Approach to Oppositional Narrative Analysis

arXiv:2603.06135v3 Announce Type: replace-cross Abstract: Distinguishing legitimate critical speech from coordinated conspiracy narratives is a pressing challenge for the integrity of the online infor

Accelerating the search for antimicrobial peptides with Google Antigravity

model-releasesgoogle-deepmind

Google Antigravity is an agentic science workbench that consolidates multiple biological databases into a single interface, enabling biologists to rapidly discover, evaluate, and prioritize therapeuti

Adaptive Computation with Conformal Certification

model-releasesarxiv-cs-lg

arXiv:2610.19189v1 Announce Type: new Abstract: Scientific imaging data involving medical (e.g., 3D radiographic, microscopic images) and astronomical sensors pose different challenges from natural im

Agents

Adaptive-Group Process Rewards for GUI Agents

arXiv:2610.17710v1 Announce Type: new Abstract: Training graphical user interface (GUI) agents with reinforcement learning suffers from sparse outcome rewards, leading to inefficient learning. Process

agentsarxiv-cs-ai

Anticipatory Evaluation of Language Models: Predicting LLM Benchmark Scores from Descriptions

model-releasesarxiv-cs-cl

arXiv:2509.20645v4 Announce Type: replace Abstract: Modern ML research increasingly faces an evaluation bottleneck: building benchmarks and running experiments is costly, slowing iteration. We ask how

Are Multimodal Benchmarks Really Useful? Item-Level Multimodal Benchmark Diagnosis via Structure-Response Co-Calibration

arXiv:2610.14542v1 Announce Type: new Abstract: Multimodal benchmarks are central to evaluating whether models can reason over information from multiple modalities. However, existing literature has re

Are We Overthinking One-Step Generation?

arXiv:2610.20331v1 Announce Type: new Abstract: Diffusion and flow matching are now dominant frameworks for generative modeling in continuous domains, but they typically require multiple network evalu

Hardware

AReaL-RSI: Adaptive Scaling and Coordination of Recursive Self-Improvement

arXiv:2610.18083v1 Announce Type: new Abstract: Scaling recursive self-improvement requires additional computation to produce useful research progress in reaching persistent objectives. Intuitively, m

hardwarearxiv-cs-ai

Back to the Future: Reverse-Consequence Modeling for Long-Horizon Particle Dynamics

arXiv:2610.18168v1 Announce Type: new Abstract: Accurate prediction of object trajectories is fundamental to mechanical understanding and robotic control. However, autoregressive models inherently suf

Budgeted KV-Cache Repair for Evolving Contexts

arXiv:2610.17338v1 Announce Type: new Abstract: Language-model agents revise their working context as information becomes obsolete, but deleting text does not erase its influence on cached computation

Hardware

capy-flash: Qwen3.8-Flash-Next (125B MoE) in full NVFP4 on two 16 GB consumer GPUs

First, kudos to Strata. It inspired this project, and while I was building it Strata got much faster and added NVFP4 support, which was my main reason for starting. By then I was too far in to stop, s

hardwarer-localllama

Chain of Time: In-Context Physical Simulation with Image Generation Models

arXiv:2511.00110v2 Announce Type: replace Abstract: We propose a novel cognitively-inspired prompting method to stabilize and interpret the physical simulation produced by autoregressive image generat

applicationsarxiv-cs-cv

Choosing the Number of Attention Heads from Intrinsic Dimension: A Small-Scale Study

arXiv:2610.19966v1 Announce Type: new Abstract: The number of attention heads in a transformer is usually set by convention or grid search. We test a simple heuristic for setting it in advance: estima

Collective Learning for Unified Robotic Manipulation via Predictive Dynamics Adaptation

arXiv:2610.19141v1 Announce Type: new Abstract: Learning a collective policy for state-based Cartesian manipulation across diverse robotic embodiments presents a fundamental challenge due to embodimen

safetyarxiv-cs-ro

Comparative Evaluation of Deep-Learning based DoA Estimators for Real-Time ISAC Beamforming

arXiv:2610.20326v1 Announce Type: new Abstract: Integrated Sensing and Communication (ISAC) systems rely on accurate Direction-of-Arrival (DoA) estimation for effective beamforming and spectral-effici

Constitutive parameterized deep energy method for solid mechanics problems with random material parameters

model-releasesarxiv-cs-lg

arXiv:2603.26030v2 Announce Type: replace Abstract: In practical structural design and solid mechanics simulations, material properties inherently exhibit random variations within bounded intervals. H

Contact-UAN: Unsupervised Actuator Networks as a Residual World Model for Humanoid Control

arXiv:2610.18991v1 Announce Type: new Abstract: Humanoid policies trained in simulation can transfer qualitatively to hardware while failing to transfer the force interactions learned during training,

applicationsarxiv-cs-ro

Copy-Paste Language Models

arXiv:2610.19247v1 Announce Type: new Abstract: Transformers are intuitively considered to be efficient at copying from their inputs. We actually show that the ability of LLMs to copy in context can b

Cross-Scenario Industrial Defect Detection via Domain-Robust Training and Metric-Aligned Selection

model-releasesarxiv-cs-cv

arXiv:2610.19540v1 Announce Type: new Abstract: Automated defect detection of industrial boards must remain highly reliable under cross-scenario variations in lighting, surface contaminants, and produ

CTIA-ODE: Continuous-Time Inter-Variable Attention for Long-Term Time Series Forecasting

arXiv:2610.19831v1 Announce Type: new Abstract: Although multivariate time series forecasting has broad application prospects, effectively incorporating exogenous variables remains challenging. Prevai

safetyarxiv-cs-lg

D2: High-Capability Full-Duplex Spoken Language Models from Half-Duplex Backbones

arXiv:2610.17124v1 Announce Type: cross Abstract: Full-duplex spoken language models (FD-SLMs) support simultaneous listening and speaking, but often lag behind half-duplex spoken language models (HD-

DAGFormer: Global Topology Prediction for Transformer Cross-Layer Connections

arXiv:2610.19625v1 Announce Type: new Abstract: We propose DAGFormer, a Transformer language model whose cross-layer connections are planned by a jointly trained topology predictor. Beyond the residua

Designing Textual Interfaces To Enhance Llm Reasoning On Audio-Visual Question Answering

model-releasesarxiv-cs-cl

arXiv:2610.20085v1 Announce Type: cross Abstract: Automatic prompt optimization (APO) has shown strong effectiveness for text-based LLMs and LLM systems, but its application to audio-visual understand

Tutorials

Do LLM Tutors Actually Teach? A Process-Centered Synthesis of the Tutoring Loop

arXiv:2610.15692v2 Announce Type: replace Abstract: Large language models can produce fluent tu- toring dialogue, but whether they actually help students learn remains unclear. We present a process-ce

tutorialsarxiv-cs-cl

Do Syntax Heads Influence Model Behavior?

arXiv:2610.19231v1 Announce Type: new Abstract: Transformer language models develop attention heads that specialize in syntactic relations, for example, attending from verbs to their subjects. Do thes

Does the Explanation Drift Before the Guarantee? Label-Free Early Warning on Evolving Graphs

arXiv:2610.16534v1 Announce Type: new Abstract: Deployed models can fail silently as the world they describe evolves. Attribution drift has served as an early warning in tabular data; we ask whether,

Don't Run with Scissors: Pruning Breaks VLA Models but They Can Be Recovered

arXiv:2510.08464v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models are a promising paradigm for field robotics, but their deployment is bottlenecked by strict edge SWaP-C co

safetyarxiv-cs-lg

Driving, Fast or Slow? Neuro-Symbolic Guidance for Motion Prediction in Multi-Modal Ground Mobility

model-releasesarxiv-cs-lg

arXiv:2606.15251v2 Announce Type: replace-cross Abstract: Accurate and interpretable motion prediction for heterogeneous traffic spaces, including pedestrians, bicycles, cars, and trucks, is essential

End-to-End Vision-Language-Action Policies for Autonomous Lunar Rover Docking

arXiv:2610.19224v1 Announce Type: new Abstract: Surface navigation on the Moon is subject to extreme illumination contrast and deployment-time perceptual disturbances. While modular navigation pipelin

safetyarxiv-cs-ro

Energy-Based Models For Speech Synthesis

arXiv:2310.12765v2 Announce Type: replace-cross Abstract: Recently there has been a lot of interest in non-autoregressive (non-AR) models for speech synthesis, such as FastSpeech 2 and diffusion model

EPOCH: Coverage-Aware Evolution with Experiential Preference Optimization for LLM-based Automated Heuristic Design

arXiv:2610.17379v1 Announce Type: new Abstract: LLM-based automated heuristic design (AHD) discovers heuristics for combinatorial optimization problems (COPs), where an LLM generates candidates in an