Search: “framework”

LLM-Augmented Bayesian Optimization with Adaptive Policies for Chiplet Design Space Exploration

arXiv:2610.14612v1 Announce Type: new Abstract: Chiplet technology is a key approach for extending Moore's Law. However, its design process is constrained by two primary challenges: the scarcity of ea

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Research

LLM-HB: Language-Aware LLM-Guided Hotword Biasing for Code-Switching ASR

DGX agent

arXiv:2610.16579v1 Announce Type: cross Abstract: Code-switching (CS) speech, characterized by language alternation within a single utterance, is prevalent in multilingual communities and poses challe

researcharxiv-cs-lg

14 Oct 2026

Load-Aware Quadruped Navigation with Online Contact-based Geometry Estimation

arXiv:2610.14596v1 Announce Type: new Abstract: Navigating cluttered environments while carrying objects remains a challenging problem for quadruped robots. Compared with works that focused on load-aw

safetyarxiv-cs-ro

Manifold Navigation Learning Using Recurrent Networks: Efficient Training Techniques

arXiv:2610.14325v1 Announce Type: new Abstract: Position tracking is a well-studied problem in Euclidean navigation, yet comparatively little attention has been given to navigation on general manifold

tutorialsarxiv-cs-cv

MERIT: Multimodal Evidence Reasoning over Image Tables

arXiv:2610.17937v1 Announce Type: new Abstract: Table reasoning with language models typically assumes access to clean textual tables. In practice, tables are often serialized into text, which can cor

safetyarxiv-cs-cv

Meta-Video: Efficient Standardized Evaluation for Video Understanding

arXiv:2610.18535v1 Announce Type: new Abstract: Video understanding benchmarks are the primary yardstick for measuring progress in video-language modeling, and a growing body of work relies on them to

MoSAIC: Learning DAG Scheduling Heuristics from Optimal Schedules through Motif-Aware Recovery and LLM-Guided Reasoning

arXiv:2610.15205v1 Announce Type: cross Abstract: Efficient task scheduling in heterogeneous computing systems remains a fundamental challenge in embedded and high-level synthesis flows. This paper pr

tutorialsarxiv-cs-lg

Neural Evidence and Behavioural Welfare Economics: When Can Neuroeconomics Inform Policy?

arXiv:2511.19548v2 Announce Type: replace Abstract: Neuroeconomics appears to offer welfare economics an evidential supplement, since neural data may help distinguish choices that express genuine pref

No Undesirable Equilibria, No Collisions: Combining Modulation and Control Barrier Functions for Liveness and Safety in Dynamic Collision Avoidance

arXiv:2502.14238v4 Announce Type: replace Abstract: Control Barrier Function Quadratic Programs (CBF-QPs) provide formal safety guarantees for general control-affine systems and accommodate actuation

safetyarxiv-cs-ro

Omni-RS: Unifying Multi-Task Understanding and Generation in Remote Sensing

arXiv:2610.18323v1 Announce Type: new Abstract: Practical remote sensing applications often require both understanding and generation capabilities for the same geographic scene. However, most existing

tutorialsarxiv-cs-cv

One-Way Coupling via Patchwise Adaptive Normalization in Transformer Surrogates

arXiv:2610.14687v1 Announce Type: new Abstract: Many physical systems exhibit one-way coupling: exogenous fields such as medium density or obstacle geometry influence the dynamics without being affect

PA-LOCO: Learning Perturbation-Adaptive Locomotion for Quadruped Robots

arXiv:2407.04224v2 Announce Type: replace Abstract: Numerous locomotion controllers have been designed based on Reinforcement Learning (RL) to facilitate blind quadrupedal locomotion traversing challe

safetyarxiv-cs-ro

PATTERN Can Be Solved from Memory: Generator-Aware Baselines for Synthetic Node Classification

arXiv:2610.15020v1 Announce Type: new Abstract: PATTERN, a synthetic node-classification benchmark still used to rank graph networks, plants a random subgraph in a random host graph and asks which nod

Agents

Persistent LLM Orchestration of Heterogeneous Robot Teams via Partial Delegation to Multi-Agent Protocols

arXiv:2610.15224v1 Announce Type: cross Abstract: Natural language specifications let non-expert users task robot teams, and large language models (LLMs) have recently proven effective at grounding su

agentsarxiv-cs-ro

Physics-Aware Object-Centric SE(3) Forecasting for Real-Time Proactive Dynamic Grasping

arXiv:2610.17843v1 Announce Type: new Abstract: Proactive dynamic grasping requires robots to predict the future state at which physical contact will occur, rather than reacting to the currently obser

applicationsarxiv-cs-ro

Pick the Mixture, Not the Samples: Combinatorial Data Selection for LLMs

arXiv:2610.14028v1 Announce Type: new Abstract: Data selection for LLM fine-tuning faces two facts about real training: data pools draw from many distinct domains, and evaluation spans diverse tasks.

Probing and Inducing Clinical Modality Grounding in Brain Tumor Segmentation

arXiv:2603.19844v3 Announce Type: replace Abstract: Multimodal MRI provides complementary information for brain tumor segmentation, but high accuracy alone does not reveal whether a model relies on cl

Provably scalable learning from quantum many-body data via locality

arXiv:2509.13705v2 Announce Type: replace-cross Abstract: Machine learning (ML) holds great promise for extracting insights from complex quantum many-body data obtained in quantum experiments, potenti

tutorialsarxiv-cs-lg

QTrack: Query-Driven Reasoning for Multi-modal MOT

arXiv:2603.13759v2 Announce Type: replace Abstract: Category-level multi-object trackers estimate trajectories for all detected instances, whereas some applications require propagating only targets sp

Hardware

Refine Where It Matters: Contact-Adaptive Meshing for Deformable Object Manipulation

arXiv:2610.14142v1 Announce Type: new Abstract: Deformable-object manipulation requires accurate modeling of highly localized contact while maintaining simulation speeds suitable for interactive use.

hardwarearxiv-cs-ro

Representational Difference Distillation

arXiv:2610.15997v1 Announce Type: cross Abstract: Knowledge distillation transfers representational knowledge from a large teacher network to a compact student. Existing relational and contrastive dis

tutorialsarxiv-cs-cv

Agents

ResearchFlow-Eval: Tracing the Execution Gap in End-to-End Multi-Claim Autoresearch

arXiv:2610.18088v1 Announce Type: cross Abstract: Autoresearch systems increasingly undertake entire research projects. In practice, scientific research requires systems to pursue multiple interdepend

agentsarxiv-cs-lg

RespFocus: Learning Temporal Evidence for Weakly Supervised Respiratory Sound Classification

arXiv:2610.15702v1 Announce Type: new Abstract: Respiratory auscultation provides a low-cost means of assessing pulmonary function, yet transient crackles and sustained wheezes can be difficult to rec

tutorialsarxiv-cs-lg

Robust Detection of Directional Adversarial Attacks in Deep Neural Networks for Radiological Imaging

arXiv:2610.15628v1 Announce Type: new Abstract: Deep learning is now central to radiology, helping detect changes on X-rays, CTs, and MRIs. However, these systems are highly vulnerable to adversarial

applicationsarxiv-cs-cv

Robust Logical Anomaly Detection under Capture Shifts via Synthetic Anomalies

arXiv:2610.18295v1 Announce Type: new Abstract: Detectors of logical anomalies, such as missing, extra or wrongly combined parts, usually score a test image by its distance from normal (good) images.

SEAR: Self-Evolving Agentic Robotics

model-releasesarxiv-cs-ro

arXiv:2610.18792v1 Announce Type: new Abstract: Frontier language-model agents can now improve robots on their own: they write control code, test it, and keep what works as skills and memories for the

SocraticRepair: Planning-Guided Socratic Tutoring for Program Debugging and Misconception Repair

arXiv:2610.15204v1 Announce Type: cross Abstract: Large language models are increasingly used in computer science education. However, the teaching abilities of even the most powerful LLMs are limited:

applicationsarxiv-cs-lg

SOVABench: A Vehicle Surveillance Action Retrieval Benchmark for Multimodal Large Language Models

arXiv:2601.04824v3 Announce Type: replace Abstract: Automatic identification of events and recurrent behavior analysis are critical for video surveillance. However, most existing content-based video r

Spectral Considerations on Unsupervised Time-domain EEG Representation Learning with Deep Networks

arXiv:2610.16264v1 Announce Type: new Abstract: Electroencephalography (EEG) is a non-invasive, scalable source of quantitative biomarkers for the early diagnosis of brain disorders, and deep represen

Sublinear Algorithms for Wasserstein and Total Variation Distances: Applications to Fairness and Privacy Auditing

arXiv:2503.07775v3 Announce Type: replace Abstract: Resource-efficiently computing representations of probability distributions and the distances between them while only having access to the samples i

TartanMatch: Towards Universal Dense Correspondence Across Modalities

arXiv:2610.14513v1 Announce Type: new Abstract: Robotic platforms combine multi-modal sensors to operate across diverse conditions, but most dense correspondence methods are limited to RGB-RGB or a sm

applicationsarxiv-cs-cv

TopoPilot: Reliable Conversational Workflow Automation for Topological Data Analysis and Visualization

arXiv:2603.25063v2 Announce Type: replace-cross Abstract: Recent agentic systems demonstrate that large language models can generate complex codebases from natural language prompts. Despite this progr

Trust Before Autonomy: Rethinking Agentic Remote Sensing for Crisis Response

arXiv:2610.18789v1 Announce Type: new Abstract: Agentic remote sensing is evaluated on how many questions it can answer, whereas crisis response depends on whether its answers can be relied on and how

Local Ai

Two Clocks: Why Larger Rollout Batches Learn Slower but Fail on Schedule in Reinforcement Learning with Verifiable Rewards

arXiv:2610.18853v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) relies on costly model-generated responses, motivating larger rollout batches and square-root lear

local-aiarxiv-cs-lg

ULPack: Reference-Conditioned Lossless Compression of Checkpoint Trajectories

arXiv:2610.14184v1 Announce Type: new Abstract: Studying model training requires checkpoint trajectories, whose storage cost limits temporal resolution. Although adjacent checkpoints are numerically c

Understanding and Mitigating Training Instability in Large-Scale Recommender Systems: A Cascade Perspective

arXiv:2610.14394v1 Announce Type: cross Abstract: Training large-scale recommender systems on dynamic industrial platforms, such as Short-Form Video (SFV) services with billions of daily interactions,

UniDeblur: Unified Motion Deblurring via Fourier Convolution Learning

arXiv:2610.12941v2 Announce Type: replace Abstract: Image deblurring is a fundamental task in computer vision, yet existing methods mainly specialize in isolated scenarios. Consequently, the deblurrin

Unrolled Neural Networks for Constrained Optimization

arXiv:2601.17274v2 Announce Type: replace Abstract: We develop unrolled neural networks to solve constrained optimization problems, offering accelerated, learnable counterparts to dual ascent (DA) alg

VisExMEM: Visual Evidence-Based Explainable Multimodal Evaluation Metric

arXiv:2610.16441v1 Announce Type: new Abstract: Current image-text evaluation often relies on a global score, which gives limited insight into which semantic details are supported by the image. Explai

VL-DocIR: A Benchmark for Vision-Based Long Document Information Retrieval

arXiv:2610.17057v1 Announce Type: cross Abstract: Vision-based document retrieval has improved rapidly, but current evaluation settings still emphasize short documents and single relevant pages. This

VLA-GAUGE: Systematically Evaluating Generalization and Robustness in Vision-Language-Action Models

arXiv:2610.16567v1 Announce Type: new Abstract: Vision-Language-Action models (VLAs) have achieved high success rates on familiar manipulation tasks, yet it remains unclear whether such scores reflect

researcharxiv-cs-cv

What Really Works for Universal Multimodal Embeddings? A Controlled Study of Contrastive Training Strategies

arXiv:2610.15035v1 Announce Type: new Abstract: Contrastive learning has become the standard paradigm for multimodal representation learning, aligning semantically matched pairs while separating misma

researcharxiv-cs-cv

Hardware

When Log Parsing Removes What Matters: Detecting Failures in Distributed GPU Workloads

arXiv:2610.14009v1 Announce Type: new Abstract: Large AI models increasingly rely on distributed GPU execution, yet it remains unclear whether established failure analysis methods transfer effectively

hardwarearxiv-cs-lg

Who Improves the Robot? Toward Physical Recursive Self-Improvement

arXiv:2610.18842v1 Announce Type: cross Abstract: Robots are increasingly autonomous in task execution, yet their improvement remains largely human-driven. This study investigates Physical Recursive S

World-T3: Test-Time Training as Persistent Memory for Real-Time Video World Models

arXiv:2610.17434v1 Announce Type: new Abstract: Recent advances in video world models have enabled plausible interactive environments, yet long-horizon generation places a fundamental demand on visual

XForecast: The KDD 2026 Finance Day Challenge on News-Grounded Financial Forecasting

arXiv:2610.16131v1 Announce Type: new Abstract: Financial forecasting has traditionally relied on numerical time-series (TS) signals, while textual information such as news remains largely underutiliz

YUBI-Real2Sim: 3DGS Scene Verification for Reliable Policy Evaluation

model-releasesarxiv-cs-ro

arXiv:2610.17521v1 Announce Type: new Abstract: Evaluating VLA policies on real robots is costly, time-consuming, and difficult to reproduce, making real-to-sim simulation essential for scalable evalu

Azure Content Understanding Prebuilt Analyzers: packaging domain knowledge for document AI