Search: “inference”

arXiv:2610.13337v1 Announce Type: cross Abstract: Attention sinks are tokens or positions that consistently receive disproportionate attention mass, often beyond what their semantic content would sugg

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Research

From Impact to Insight: Dynamics-Aware Proprioceptive Terrain Sensing on Granular Media

DGX agent

arXiv:2604.02563v2 Announce Type: replace Abstract: Robots that traverse natural terrain must interpret contact forces generated under highly dynamic conditions. However, most terrain characterization

researcharxiv-cs-ro

12 Oct 2026

GeoFitBench-LLM: A Benchmark for Assessing Large Language Models' Capabilities in Geospatial Data Requirements Elicitation for Geo-Analytic Tasks

arXiv:2610.12669v1 Announce Type: cross Abstract: Large language models are becoming central to GeoAI systems, yet their evaluation rarely considers the elicitation of geospatial data requirements. Th

GIST: Generator-state-Informed Supervision for Tabular Foundation Models

arXiv:2610.12904v1 Announce Type: new Abstract: Tabular foundation models (TFMs) based on prior-data fitted networks typically use sampled hard query labels, leaving avoidable sampling variability in

Humanize Olympiad Agents: A Multi-Session Workflow for Olympiad Problem Solving with Solve, Review, Wiki, Verify

arXiv:2610.13632v1 Announce Type: new Abstract: Large language model (LLM) agents are rapidly improving on long-horizon scientific and olympiad tasks. Recent systems have produced a Lean-formalized re

Knowing When to Stop: Efficient Context Processing via Latent Sufficiency Signals

arXiv:2502.01025v4 Announce Type: replace Abstract: Large language models (LLMs) process entire input contexts indiscriminately, which is inefficient when the information required to answer a query is

Kronecker Product Attention: Memory-Efficient KV Compression via Structured Factorization

arXiv:2610.12657v1 Announce Type: cross Abstract: Efficient autoregressive generation is increasingly limited by the memory footprint of the key-value (KV) cache, which grows linearly with sequence le

researcharxiv-cs-ai

LeapBot-JAC: Joint Action Chains for World Action Models

arXiv:2610.12886v1 Announce Type: new Abstract: Action-chunking policies predict future controls but execute only a prefix before replanning. How should a fixed action-token budget be organized to sup

applicationsarxiv-cs-ro

Lightweight Time-Frequency Vibration Sensing for Consumer Device Condition Monitoring

arXiv:2610.13040v1 Announce Type: cross Abstract: Consumer rotating devices, including washing machines, air conditioners, electric fans, robotic vacuum cleaners, and home fitness equipment, increasin

Machine Learning and Time-Series Foundation Models for Day-Ahead Electricity Forecasting in a University Building

arXiv:2610.12638v1 Announce Type: cross Abstract: Day-ahead electricity forecasts can help building operators schedule heating, ventilation, and other services around anticipated demand. Choosing a fo

Masked Diffusion Language Agents for Tool-Integrated Chemical Reasoning

arXiv:2610.13330v1 Announce Type: new Abstract: Designing tool-integrated reasoning agent systems for complex chemical tasks remains a fundamental challenge. Although recent chemical agents have demon

Mixture of Many Zero-Compute Experts: A High-Rate Quantization Theory Perspective

arXiv:2510.03151v2 Announce Type: replace Abstract: This paper uses classical high-rate quantization theory to provide new insights into mixture-of-experts (MoE) models for regression tasks. Our MoE i

MolP2SBench: Do LLMs Really Reason from Molecular Properties to Structure?

arXiv:2610.12522v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in molecular discovery and structure elucidation, where decisions depend on physical observations.

Monarch-MoE: Structured Experts for Multimodal Continual Instruction Tuning

arXiv:2610.13215v1 Announce Type: new Abstract: Learning new tasks in multimodal continual instruction tuning can cause catastrophic forgetting of previously acquired knowledge. Although multi-expert

Tutorials

MVNN: A Measure-Valued Neural Network for Learning McKean-Vlasov Dynamics from Particle Data

arXiv:2604.00333v3 Announce Type: replace-cross Abstract: Collective behaviors that emerge from interactions are fundamental to numerous biological systems. To learn such interacting forces from obser

tutorialsarxiv-cs-lg

Neurograf v1: An End-to-End Romanian-First Language Model Family

arXiv:2610.13134v1 Announce Type: new Abstract: We present Neurograf v1, an experimental end-to-end Romanian-first language-model pipeline developed to investigate the feasibility of training language

Hardware

Neuromorphic Satellite Intelligence: A Formal Framework for Event-Driven Architectures, Spike-Based Algorithms, and Quantitative Energy-Accuracy Trade-offs

arXiv:2610.12471v1 Announce Type: cross Abstract: Satellite onboard computing faces an irreducible tension: mission intelligence requirements grow monotonically while power, mass, and radiation budget

hardwarearxiv-cs-lg

Non-Prehensile Multi-Object Placement with Mobile Robots via Diffusion-Based Trajectory Planning

arXiv:2610.12684v1 Announce Type: new Abstract: Non-prehensile manipulation with mobile robots has primarily targeted placement in coarse goal regions. Precision placement has been studied with manipu

safetyarxiv-cs-ro

NovaSplat: Model-Free 6D Object Pose Estimation via 3D Gaussian Splatting Onboarding and Refinement

model-releasesarxiv-cs-ro

arXiv:2610.13309v1 Announce Type: cross Abstract: 6D pose estimation of novel objects without CAD models remains an open challenge: model-free methods must build the object representation from scratch

NV-Tesseract-AD: Curriculum-Enhanced Conditional Diffusion for Multivariate Time-Series Anomaly Detection

arXiv:2610.12754v1 Announce Type: new Abstract: We propose NV-Tesseract-AD, a curriculum learning-enhanced conditional diffusion framework for multivariate time-series anomaly detection. Our central h

OccludeBench: Can VLMs Find What's Missing?

arXiv:2610.13790v1 Announce Type: cross Abstract: How well can vision-language models (VLMs) reason about what is missing from an image? We study this question with OccludeBench, a manually curated be

Oido: Open-Vocabulary Speech Recognition on a $5 Microcontroller without a Neural Accelerator

arXiv:2610.13447v1 Announce Type: cross Abstract: Speech recognition on low-cost microcontrollers is, in practice, limited to keyword spotting or a fixed list of commands. We present Oido, an inferenc

On the Design Space of Continuous Diffusion Language Models

arXiv:2610.13834v1 Announce Type: new Abstract: Continuous diffusion language models (CDLMs) promise to bring the benefits of continuous flow modelling to language, including accelerated sampling and

On the Encoding of Calendar Features in Covariate-Informed Time Series Foundation Models

arXiv:2610.13676v1 Announce Type: new Abstract: Time series foundation models (TSFMs) increasingly offer covariate support, with calendar information being the most common type of categorical covariat

Orthros: Phase-Aware Heterogeneous Attention for Efficient Transformers

arXiv:2610.13735v1 Announce Type: cross Abstract: Efficient attention mechanisms, such as linear and sliding window attention, aim to reduce the computational complexity of Transformers from quadratic

applicationsarxiv-cs-ai

Agents

PACT: Privileged Trace Co-Training for Multi-Turn Tool-Use Agents

arXiv:2606.16215v2 Announce Type: replace-cross Abstract: Multi-turn tool-use agents must reason, call tools, and adapt to observations across several interaction turns. Post-training such agents is c

agentsarxiv-cs-ai

Agents

Prediction-Informed Landing Window Planning for UAV Landing on USV in High Sea States

arXiv:2610.13190v1 Announce Type: cross Abstract: Autonomous landing of unmanned aerial vehicle (UAV) on unmanned surface vehicle (USV) is difficult in high sea states. Existing hierarchical landing m

agentsarxiv-cs-lg

PVBRF-ID: Private, Verifiable and Byzantine-Robust Federated Intrusion Detection for Oilfield Enterprise Networks

arXiv:2610.12704v1 Announce Type: cross Abstract: Federated learning allows dispersed oilfield sites to train a shared intrusion detector without pooling network traffic, yet its aggregation step forc

applicationsarxiv-cs-lg

RATED: Reliability-Aware AI Agent Tool Retrieval via Execution Dynamics

arXiv:2610.13889v1 Announce Type: new Abstract: As AI agents increasingly rely on external tools, accurate retrieval is essential for reliable behavior. Existing methods optimize semantic relevance bu

Rationally Linearized MLPs

arXiv:2610.13568v1 Announce Type: new Abstract: We present Rationally Linearized Multilayer Perceptrons(RaLiMPs), a new approach to efficiently linearizing MLPs using low-degree rational approximation

Realism VS Accuracy: Event Sequence Forecasting from a Generative Modeling Perspective

arXiv:2610.12586v1 Announce Type: new Abstract: Event sequences are chains of random events, each described by heterogeneous (numerical and categorical) features. The problem of event sequence forecas

Reflex: Visually Grounded Reactive Humanoid Control

arXiv:2610.12772v1 Announce Type: new Abstract: Humans effortlessly react to the world; they adeptly return a tennis shot, catch a falling cup, step aside from a passing cart, or pass a box tossed dur

safetyarxiv-cs-ro

ReSFlow: Rectifying Categorical Flows on Statistical Manifolds for One-Step Generation

arXiv:2610.13225v1 Announce Type: cross Abstract: Generative modeling for discrete data has been significantly advanced by learning continuous vector fields on the statistical manifolds to transport s

applicationsarxiv-cs-ai

Retrieval-Augmented Multimodal Language Model with Heterogeneous Evidence Integration for Clinical Prognosis

arXiv:2610.13510v1 Announce Type: new Abstract: Clinical prognosis requires integrating structured measurements, physiological waveforms, longitudinal history, and population context. We introduce PRI

SmolWAM: A Latent World-Action Model for Robotic Manipulation on Edge Devices

arXiv:2610.13740v1 Announce Type: cross Abstract: World-action models (WAMs) predict a robot's actions together with the observations those actions will produce. However, the strongest models rely on

Spanning Diffusion and Flow-based Posterior Sampling via Exact Gaussian Conditioning

arXiv:2610.13812v1 Announce Type: new Abstract: Flow-matching and diffusion models are increasingly used as priors for linear inverse problems, however, most methods are bespoke to one class of trajec

SWEAR: Section-Wise Efficient Audio Reasoning via Self-Rated Difficulty

arXiv:2610.13081v1 Announce Type: new Abstract: Recent work on large audio-language models (LALMs) explores adaptive reasoning to balance accuracy and efficiency. However, existing approaches often re

researcharxiv-cs-ai

Agents

SynAct: Synergistic Active Feedback Learning for LLM Agents

arXiv:2610.12651v1 Announce Type: new Abstract: LLM agents executing multi-step workflows fail in two fundamentally different ways: recoverable slips, which further attempts can repair, and knowledge

agentsarxiv-cs-lg

Hardware

Tabular Foundation Models Are Effectively Shallow

arXiv:2610.13253v1 Announce Type: cross Abstract: In-context-learning Tabular Foundation Models (TFMs) are uniquely suited to scenarios with limited resources or privacy constraints, as they solve new

hardwarearxiv-cs-ai

Transformer-based In-Context Score Operator Learning for Diffusion Models

arXiv:2610.13690v1 Announce Type: new Abstract: Diffusion models typically learn the generative dynamics of a single target distribution or a family of distributions indexed by conditioning variables

VEPA: Verified Evolving Formal Policy for Lifelong LLM Agent Guardrails

arXiv:2610.12813v1 Announce Type: new Abstract: LLM agents increasingly operate over sensitive resources, such as private documents and mutable system states, which can create serious safety and secur

safetyarxiv-cs-ai

WoundAmbit: Bridging State-of-the-Art Semantic Segmentation and Real-World Wound Care

arXiv:2504.06185v3 Announce Type: replace-cross Abstract: Chronic wounds affect a large population, particularly the elderly and diabetic patients, who often exhibit limited mobility and co-existing h

Your Discrete Graph Diffusion Model is Secretly Memorizing

arXiv:2610.13786v1 Announce Type: cross Abstract: Discrete graph diffusion models (GDMs) corrupt the graph structure by adding noise independently to nodes and edges under a Markovian noise model. In

safetyarxiv-cs-ai

A 3D Characterization Framework for Intelligent Sequential Decision Making

arXiv:2610.11696v1 Announce Type: new Abstract: Puzzles are widely used to evaluate the reasoning capabilities of artificial intelligence (AI) systems for sequential decision making, yet approaches or

A Geometric Approach to Soft Actor-Critic with Zonotopes for Locomotion Learning

arXiv:2610.12113v1 Announce Type: cross Abstract: Off-policy actor--critic methods control overestimation bias by taking the minimum of two critics. This uses the same aggregation rule everywhere, reg

safetyarxiv-cs-ai

A Minimal Optical-Flow Representation for Vision-Based Tactile Rotation Classification in Robotic Manipulation Across Gravity Domains

arXiv:2610.12073v1 Announce Type: cross Abstract: Vision-based tactile sensors provide rich contact information, but processing high-resolution images can be costly for resource-constrained platforms

researcharxiv-cs-cv

A Structural Theory of Cognitive Representation and Problem Solving,Contexts, Invariance, and the Knowledge Space

arXiv:2610.12306v1 Announce Type: new Abstract: Learning and problem solving depend critically on the structure of internal representations. While many modern data-driven artificial systems achieve st

researcharxiv-cs-ai

A Survey on LLM-Integrated Hardware Design Verification

arXiv:2610.10580v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly being integrated into hardware verification to automate specification interpretation, verification-artif