Search: “models”

arXiv:2608.01670v1 Announce Type: new Abstract: This paper answers the one-dimensional local root anti-concentration questions posed by Balcan, Pegden, and Sharma in the context of online optimization

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Hardware

SparseKAN: Compressing Kolmogorov--Arnold Networks Across Basis Functions, Neurons, and Bits

DGX agent

arXiv:2608.00859v1 Announce Type: new Abstract: Kolmogorov--Arnold Networks (KANs) replace scalar edge weights with learnable univariate functions parameterized by multiple basis coefficients. This in

hardwarearxiv-cs-lg

4 Aug 2026

SSTG-Nav: Metric-Grounded Spatial-Semantic Topological Graphs for Reusable Object Navigation

arXiv:2608.00527v1 Announce Type: new Abstract: Service robots operating for months in the same homes, offices, and facilities should become more reliable with experience instead of searching familiar

Statistical Mechanics of Learning on Product Wasserstein Manifolds

arXiv:2608.01434v1 Announce Type: new Abstract: Normally the statistical mechanics of learning treats constraints on weight distributions as restrictions that shrink the space of possible solutions. T

Stochastic Sequential Search in Very-High-Dimensional Feature Selection

arXiv:2608.01502v1 Announce Type: cross Abstract: Sequential subset search -- forward selection with floating backtracking and its descendants -- remains the quality reference in feature selection, bu

SWE-Touch: Benchmarking Coding Agents When Users Touch the Code

arXiv:2608.02499v1 Announce Type: cross Abstract: Real-world software development requires coding agents to operate in shared workspaces where users may inspect and modify code during an ongoing task,

agentsarxiv-cs-cl

tFUSOperator: Operator Learning for Transcranial Focused Ultrasound Digital Twins

arXiv:2608.01839v1 Announce Type: new Abstract: Transcranial focused ultrasound (tFUS) requires accurate estimation of the intracranial acoustic field, which is distorted by skull-induced aberrations.

The 1st AI Children Challenge

arXiv:2608.00356v1 Announce Type: new Abstract: The First AI Children Challenge aims to advance real-world applications of computer vision and AI in child healthcare, child education, and pediatrics.

applicationsarxiv-cs-cv

The Fourth Quadrant: A Stylized View of Benign Misfitting

arXiv:2608.01032v1 Announce Type: new Abstract: Training error is what we can observe on a training set; test error is the quantity we actually care about. We study linear regression with squared-erro

The Label Defines the Timescale: Trait-State Limits of Temporal-Aggregate Learning

arXiv:2608.01587v1 Announce Type: cross Abstract: Machine-learning benchmarks often pair a label that aggregates a long temporal horizon with input observed through one or a few short windows. Their a

Think in Sets for Streaming Video Token Compression

arXiv:2608.01169v1 Announce Type: new Abstract: Streaming VideoLLMs process frames causally while visual tokens grow continuously, making compression essential for controlling prefilling latency and m

Towards a theory of morphology-driven marking in the lexicon: The case of the state

arXiv:2604.03422v2 Announce Type: replace Abstract: All languages have a noun category, but its realisation varies considerably. Depending on the language, semantic and/or morphosyntactic differences

researcharxiv-cs-cl

Training Small LLMs as Spatial Multi-Agent Policies

arXiv:2608.01425v1 Announce Type: cross Abstract: Training LLM-based multi-agent systems with multi-agent reinforcement learning is rapidly gaining traction, and a parallel line of work argues that su

Trajectories That Segment Themselves: Agent-Declared Boundaries as a Training Unit

arXiv:2608.02302v1 Announce Type: cross Abstract: Long-horizon coding-agent trajectories are poorly matched to the credit units available to train on: a single action has no stable value, an episode l

agentsarxiv-cs-lg

Trustworthy AI in Digital Health: A Comprehensive Review of Robustness and Explainability

arXiv:2608.02238v1 Announce Type: cross Abstract: Ensuring trust in AI systems is essential for the safe and ethical integration of machine learning systems into high-stakes domains such as digital he

Uncertainty-guided active learning for surrogate prediction of stream-finishing wear fields

arXiv:2608.00593v1 Announce Type: cross Abstract: In stream finishing, the wear experienced by a workpiece depends strongly on its orientation within the rotating abrasive media. Determining suitable

Uncertainty Quantification for Visual Object Pose Estimation: S-Lemma Ellipsoidal Bounds

arXiv:2511.21666v2 Announce Type: replace-cross Abstract: Quantifying the uncertainty of an object's pose estimate is essential for robust control and planning. Although pose estimation is a well-stud

applicationsarxiv-cs-cv

UniMoCa: Unifying Motion and Camera Controls as Visual Proxies for Faithful Human Video Generation

arXiv:2608.01944v1 Announce Type: new Abstract: Controlling human motion and camera movement is essential for faithful human-oriented video generation, yet remains challenging in multi-person scenes w

Verification Without Sufficiency: Per-Chunk Filtering Fails on Multi-Hop RAG, and Decomposition Repairs It

arXiv:2608.00585v1 Announce Type: new Abstract: Verification for retrieval-augmented generation usually scores each retrieved chunk and drops the ones that fail. We show this cannot work for multi-hop

researcharxiv-cs-cl

What Could the Agent See at 19:05? Generating Temporal Enterprise Scenarios from Real Research and Replaying Them to Evaluate Agents

arXiv:2608.01042v1 Announce Type: cross Abstract: Enterprise AI agents act across many apps whose data changes continuously, so an answer is correct only relative to what data existed and who could se

agentsarxiv-cs-lg

When Extreme Darkness Meets Motion Blur: MeanFlow for Unified RAW Restoration

arXiv:2608.01720v1 Announce Type: new Abstract: Extremely low-light RAW enhancement aims to recover severely attenuated sensor signals, yet existing methods often focus on illumination and noise while

Why Does Action Chunking Improve Behavioral Cloning Performance in Robotic Control?

arXiv:2608.02547v1 Announce Type: new Abstract: Action chunking---predicting and executing multiple actions instead of a single action---has proven to be a critical component for learning effective ro

safetyarxiv-cs-ro

xMICD: Explainable Representation of Multiple ICD Codes

arXiv:2608.00935v1 Announce Type: new Abstract: Electronic Health Records (EHRs) are widely used for clinical risk prediction using machine learning. International Classification of Diseases (ICD) cod

Local Ai

A Biometric Sensor Network to Enable Real-Time Measurement of Individual Student Engagement in STEM Lecture Environments

arXiv:2607.28944v1 Announce Type: cross Abstract: Student engagement (SE) is a critical predictor of academic performance and retention in STEM education, yet existing measurement approaches are often

local-aiarxiv-cs-cv

A Machine Learning Surrogate for Component Criticality Ranking in Interdependent Power-Communication Networks

arXiv:2607.08918v2 Announce Type: replace Abstract: Cyber-physical power systems are vulnerable to cascading failures caused by interdependencies between power and communication infrastructures. Becau

A Neurosymbolic Approach for Explainable Early Diagnosis of Alzheimer's Disease

arXiv:2607.29530v1 Announce Type: new Abstract: Identifying reliable Alzheimer's disease (AD) markers typically requires manual, labor-intensive transcription and expert analysis, limiting its scale.

Tutorials

A user's guide to PINNs in geometric analysis: lessons from the asymptotic Plateau problem

arXiv:2607.28733v1 Announce Type: cross Abstract: This proceedings contribution elaborates on the findings of arXiv:2605.26234v2: a joint work with Marco Usula, where we introduced a machine learning

tutorialsarxiv-cs-ai

Adaptive FastOPD: Progress-Aware Rollout Horizon Expansion for Efficient On-Policy Distillation

arXiv:2607.29494v1 Announce Type: new Abstract: On-policy distillation (OPD) provides dense teacher supervision along student-generated trajectories, but its online rollout process incurs substantial

Analysing User Reviews to Identify User Concerns Around Permissions in AI Apps

arXiv:2607.29343v1 Announce Type: new Abstract: Artificial intelligence is increasingly embedded in everyday software, making its integration into mobile apps inevitable. However, AI mobile app develo

AuEmoChat: Authentic Emotion Understanding and Rendering for Conversational Speech Synthesis

arXiv:2607.15755v2 Announce Type: replace-cross Abstract: Conversational Speech Synthesis (CSS) aims to synthesize speech with human-like emotional expression and contextual consistency in user-agent

agentsarxiv-cs-ai

Authorship Verification of Transcribed German-Language Videos

arXiv:2607.29168v1 Announce Type: new Abstract: Authorship Verification (AV) represents an important subfield of digital text forensics and addresses the fundamental question of whether two texts were

researcharxiv-cs-cl

Balancing of Humanoid with Object Mass: Trade-off Analyses and Lifting Control

arXiv:2607.29625v1 Announce Type: new Abstract: The demand for humanoid loco-manipulation tasks with an object has recently increased, and most existing control approaches for stability in such tasks

Beyond Black-Box Advice: Learning-Augmented Algorithms for MDPs with Q-Value Predictions

arXiv:2307.10524v3 Announce Type: replace Abstract: We study the tradeoff between consistency and robustness in the context of a single-trajectory time-varying Markov Decision Process (MDP) with untru

CalibratedRubric: Task-Adaptive Rubric Banks for Open-Ended LLM Evaluation

arXiv:2607.29252v1 Announce Type: cross Abstract: Reliable evaluation of open-ended LLM outputs requires fine-grained rubrics, yet expert curation is costly and difficult to scale. Existing automated

applicationsarxiv-cs-ai

Code Is the Body: Agent-Owned Software Bodies for Recursive Evolution and Descent

arXiv:2607.28691v1 Announce Type: cross Abstract: Personalized AI agents are often configurable without giving users control over the artifacts that determine their future behavior. We present OurArk,

agentsarxiv-cs-ai

ConnectED: A Curriculum-Aligned AI System for Vietnamese Instructional Lesson Planning and Student Learning

arXiv:2607.28647v1 Announce Type: cross Abstract: This paper presents ConnectED, a human-centered AI system that supports the full instructional lifecycle in Vietnamese education by linking curriculum

safetyarxiv-cs-ai

Tutorials

Contrastive Learning for Image Complexity Representation

arXiv:2408.03230v2 Announce Type: replace Abstract: Quantifying and evaluating image complexity can be instrumental in enhancing the performance of various computer vision tasks. Supervised learning c

tutorialsarxiv-cs-cv

Local Ai

CPInj: Uncovering Prompt Injection Risks in Textual Collaborative Prompt Optimization

arXiv:2607.18622v2 Announce Type: replace-cross Abstract: Textual Collaborative Prompt Optimization (TCPO) extends TextGrad (Yuksekgonul et al., 2025) to a decentralized setting by allowing multiple c

local-aiarxiv-cs-ai

Cross-Resolution Semantic Learning for Graph Domain Adaptation

arXiv:2607.29365v1 Announce Type: new Abstract: Graph Domain Adaptation (GDA) transfers predictive knowledge from labeled source graphs to unlabeled target graphs under distribution shift. Existing me

D-VLC: Decentralized Vision-Language Collaboration for Heterogeneous Embodied Multi-Robot Systems in Unknown Environments

arXiv:2607.29009v1 Announce Type: new Abstract: Multi-robot systems, particularly heterogeneous robot swarms, can improve the efficiency of complex task execution through parallel collaboration and co

Hardware

DeltaServe: Host-Agnostic Co-Serving of Inference and Fine-Tuning for LLMs

arXiv:2607.28848v1 Announce Type: cross Abstract: LLM serving systems are provisioned for peak load to meet strict latency targets, leaving substantial GPU compute idle whenever traffic falls below pe

hardwarearxiv-cs-lg

DragonCrawl: A Generative, Intent-Based Framework for Scalable Mobile End-to-End Testing

arXiv:2607.28750v1 Announce Type: cross Abstract: As mobile applications grow in complexity, traditional End-to-End (E2E) testing frameworks struggle with UI volatility, maintenance overhead, and cros

applicationsarxiv-cs-ai

EduPanel: A Three-Agent LLM Judge for Teaching Videos -- Reliability, Complementarity, and Human Trust Calibration

arXiv:2607.18529v2 Announce Type: replace-cross Abstract: Teaching videos are becoming a major medium for education, creating a growing need for scalable evaluation of their pedagogical quality. Exist

agentsarxiv-cs-ai

Exploring Block Anomaly Detection In HDFS Log Data Analysis

arXiv:2607.29383v1 Announce Type: new Abstract: In recent years, with the development of big data technology, increasingly more companies use HDFS for data processing and storage. As a result, the mai

FairDiffuseVQVAE: Sampling-Time Fairness in Tabular Diffusion via Conditional Refinement of Vector-Quantized Latents

arXiv:2607.28945v1 Announce Type: new Abstract: Synthetic tabular data is increasingly used in privacy-preserving data sharing, data augmentation, and to mitigate downstream classifier bias. State-of-

FillGS: Filling Observation Gaps in 4D Gaussian Splatting via Viewpoint-Time Selection and Generative Refinement

arXiv:2607.29284v1 Announce Type: new Abstract: 4D Gaussian Splatting (4DGS) can render dynamic scenes photorealistically. However, with limited viewpoint coverage, some spatiotemporal regions remain

GPA-RAM: Grasp-Pretraining Augmented Robotic Attention Mamba for Spatial Task Learning

arXiv:2504.19683v4 Announce Type: replace Abstract: Fine-grained robotic manipulation often fails when inaccurate initial grasps propagate errors and necessitate complex pose correction. We propose Gr

Hardware

GPU-Accelerated ANNS: Quantized for Speed, Built for Change

arXiv:2601.07048v5 Announce Type: replace-cross Abstract: Approximate nearest neighbor search (ANNS) is a core problem in machine learning and information retrieval applications. GPUs offer a promisin

hardwarearxiv-cs-ai