Search: “routing”

CLAIR-Fin: An Adversarial Multi-Agent Framework for Claim-Level Verification and Adaptive Debate in Cross-Modal Financial QA

arXiv:2608.13706v1 Announce Type: cross Abstract: Existing defenses against hallucination in retrieval-augmented and multi-agent pipelines remain partial: evidence is trusted despite modality disagree

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Research

Communication in modular robotic motor control: Bilateral controllers under realistic constraints

DGX agent

arXiv:2608.13904v1 Announce Type: new Abstract: Robotic motor control in musculoskeletal systems requires fast, accurate movement and robust postural stabilization under signal-dependent noise (where

researcharxiv-cs-ro

17 Aug 2026

Consensus-gated Multi-Agent Neural Architecture Search for Seismic Fault Segmentation

model-releasesarxiv-cs-cv

arXiv:2608.13889v1 Announce Type: new Abstract: Neural networks for seismic fault segmentation are often borrowed from computer vision and medical imaging domains where they train under relatively muc

Contrastive Learning for Interpretable Anomaly Detection at Collider Experiments

arXiv:2608.13652v1 Announce Type: new Abstract: Generic event-level anomaly detection for collider physics has two recurring problems: anomaly scores are hard to interpret, and they correlate strongly

researcharxiv-cs-lg

CRAFT: Constrained Reward via Attention Fine-Tuning for Subject Personalization without Composed Targets

arXiv:2608.14403v1 Announce Type: new Abstract: Subject-driven image personalization---generating new images that preserve the identity of one or several reference subjects in novel scenes---is a foun

LLMs Don't Pay for the Jump

arXiv:2608.14397v1 Announce Type: new Abstract: Zahavy [2026] argues that Large Language Models, despite their capabilities in induction and deduction, cannot perform the abductive 'Jump' that produce

researcharxiv-cs-ai

Marionette: Predicting World States, Rendering Geometry, Painting Appearance

arXiv:2608.14530v1 Announce Type: cross Abstract: Interactive game world models typically autoregress visual observations directly in pixel or latent space, forcing structured properties such as pose,

Tutorials

No Universal Signal Predicts Sample-Level LLM Regression under Version Updates

arXiv:2608.13607v1 Announce Type: new Abstract: Frontier LLMs are updated frequently and typically outperform their predecessors in aggregate. But aggregate gains say little about individual samples:

tutorialsarxiv-cs-ai

Non-Parametric Spatiotemporal Trajectory Prediction via State-Conditioned Transition Sampling

model-releasesarxiv-cs-lg

arXiv:2608.14349v1 Announce Type: new Abstract: We present a training-free method for multi-modal trajectory prediction that achieves comparable accuracy to a 57M-parameter transformer while requiring

P2Skill: Privacy Preserving Skill Distillation for Cloud-Local LLM Inference Systems

arXiv:2608.14094v1 Announce Type: cross Abstract: Cloud-local LLM inference systems have the potential to use the reasoning capability of large cloud models while protecting sensitive user data on per

Regime-Conditional Verification: Correctness Estimation for Adapting and Monitoring Safety Classifiers

arXiv:2608.14089v1 Announce Type: new Abstract: Safety classifiers deployed with large language models often fail for two reasons: their decisions reflect the policy learned during training rather tha

Local Ai

SCVIB: Editable State-Conditioned Visual Instance Binding forMulti-Turn Personalized Localization

arXiv:2608.14148v1 Announce Type: new Abstract: We introduce editable state-conditioned visual instance binding, a multi-turn localization setting in which several support-defined instances are introd

local-aiarxiv-cs-cv

Simulation-Aware In-Context Policy Improvement for LLM-Aided Analog Layout Refinement

arXiv:2608.13767v1 Announce Type: new Abstract: Analog IC layout design remains a labor-intensive iterative process dominated by simulation-driven refinement. Although end-to-end layout generators acc

TeachMateGPT: A Multi-Agent Knowledge-Grounded Framework for Pedagogical Assessment Generation from Science Curriculum Materials

arXiv:2608.13708v1 Announce Type: cross Abstract: Automatically generating textbook-grounded assessment items can reduce science teachers' workload, but existing retrieval-augmented generation (RAG) s

VoiceChat-TTS: A Low-Latency Continuous Speech Synthesis Model for Interactive Agents

arXiv:2608.13831v1 Announce Type: cross Abstract: Spoken dialogue is a natural form of human--computer interaction, yet most speech language models remain limited to turn-based operation and lack real

researcharxiv-cs-cl

BoardroomAI: Dependency-Aware Human-Steerable Multi-Agent Deliberation through Evolving Decision Graphs

arXiv:2608.13046v1 Announce Type: new Abstract: Organizational decisions are co-created while evidence, constraints, and human priorities continue to evolve. In conventional transcript-based multi-age

BrainWAM: Action-Space Coordination of Semantic Priors and Predictive Dynamics for Autonomous Driving

arXiv:2608.12854v1 Announce Type: cross Abstract: Autonomous driving requires planning under both semantic constraints and predictive dynamics. Existing end-to-end driving approaches, however, typical

Capstan-driven Continuum Surgical Robot: Design, Modeling, and Perception

arXiv:2608.13396v1 Announce Type: new Abstract: Shape and force sensing have long been critical bottlenecks in the development of compact capstan-driven continuum surgical robots, primarily due to the

researcharxiv-cs-ro

ContactGuard: Pre-Contact Execution Monitoring with Action-Conditioned Latent World Models

arXiv:2608.13438v1 Announce Type: cross Abstract: Contact-rich manipulation failures are often detected only after the robot has committed to contact. This is especially limiting in wrist-camera setup

Decomposition of Evidence, Contradiction, and Fragility in Perturbation Responses

arXiv:2608.12935v1 Announce Type: new Abstract: Perturbation methods explain model decisions by measuring prediction changes under altered inputs, but response magnitude tells us only how much a model

researcharxiv-cs-ai

EgoMonth: A Month-Level Egocentric Video Benchmark for Long-Term Spatiotemporal Memory

arXiv:2608.13113v1 Announce Type: cross Abstract: Recent advances in Multimodal Large Language Models (MLLMs) have led to substantial progress in video understanding, accompanied by a growing number o

Hardware

Enhancing Virtual Agents through SLMs and Edge-Computing: An Exploratory Evaluation of Think and Memory Processes

arXiv:2608.13420v1 Announce Type: new Abstract: Embodied intelligent virtual agents are expected to operate as persistent, adaptive, and context-aware entities within complex virtual and Metaverse wor

hardwarearxiv-cs-ai

Fine-Grained Action Recognition with Cross-Attentive Latent Sparse Experts

arXiv:2608.13458v1 Announce Type: new Abstract: Fine-grained human action recognition (FHAR) must distinguish visually similar actions that differ mainly in body configuration, timing, or local appear

FIRE-VLA: Failure-Informed Self-Evolution for Vision-Language-Action Models in Autonomous Driving

model-releasesarxiv-cs-ro

arXiv:2608.13395v1 Announce Type: new Abstract: Reinforcement learning improves autonomous-driving vision-language-action (VLA) models by evaluating trajectories sampled from the current policy. Group

Reconcile Once, Write Anytime: A Trust-Tiered Librarian and a Multi-Agent Writer for Drift-Free, Point-in-Time Research

arXiv:2608.12984v1 Announce Type: cross Abstract: Long-form research reports generated by large language models drift, contradict themselves, and lose provenance: the same metric appears with differen

safetyarxiv-cs-cl

Refusing Intent, Not Form: Wrapper-Based Intent-Group Supervision for LLM Safety

model-releasesarxiv-cs-cl

arXiv:2608.13304v1 Announce Type: new Abstract: Safety tuning can improve harmful refusal, but models may learn surface-form shortcuts: wrapped harmful prompts bypass safety, while similarly wrapped b

Represent, Then Generate: Multimodal-Conditioned Time-Series Generation under Irregular Missingness

arXiv:2608.12592v1 Announce Type: new Abstract: Continuous physiological time series underpin modern clinical monitoring, yet many of the most informative signals are invasive, expensive, or simply un

researcharxiv-cs-lg

Simulation-to-real transfer learning for infrared spectroscopic chemical sensing and analysis from molecules to complex samples

arXiv:2608.13341v1 Announce Type: cross Abstract: Infrared (IR) spectroscopy is widely used for chemical sensing, but extracting reliable chemical information from spectra remains challenging. Convent

Applications

SPADE: Speculative Decoding for Precise and Low Cost Distributed Edge Cloud Inference

arXiv:2608.13076v1 Announce Type: new Abstract: Large Language Models (LLMs) have achieved remarkable success in natural language understanding and generation, but their deployment is constrained by h

applicationsarxiv-cs-ai

Tutorials

Sparse Orthogonal Regression Technique: A Spectral Framework for Equation Discovery, Approximation, and Integration

arXiv:2608.13504v1 Announce Type: new Abstract: We develop the Sparse Orthogonal Regression Technique (SORT), a sparse spectral framework for learning orthonormal-basis expansions from noisy and irreg

tutorialsarxiv-cs-lg

VALG: An Agentic System for ML Theory Research

arXiv:2608.13060v1 Announce Type: new Abstract: Machine learning theory studies learning procedures through mathematical setups in which the data model, training protocol, oracle access, loss, metric,

When Is a Task Vector Enough? An Empirical Theory of Implicit Multimodal ICL

arXiv:2608.13385v1 Announce Type: new Abstract: Implicit multimodal in-context learning compresses demonstrations into internal interventions, ranging from static task vectors to query-conditioned tra

A Modular Agentic Framework for Synthetically Constrained Multi-Objective Hit-to-Lead Optimization

arXiv:2608.11483v1 Announce Type: new Abstract: Hit-to-lead optimization requires iterative design of hit analogs across competing potency, selectivity, physicochemical, pharmacokinetic, safety, and s

Advancing MLLM-based UAV Image Understanding and Reasoning: A Benchmark and a Training-Free Multi-Agent System

arXiv:2608.11738v1 Announce Type: cross Abstract: Multimodal Large Language Model (MLLM)-based UAV aerial image understanding and reasoning is essential for aerial intelligence yet poses distinct chal

AI4AI at Test-Time: Strong-to-Weak Capability Transfer via Harnesses

arXiv:2608.12307v1 Announce Type: cross Abstract: Recent work on distillation transfers the capabilities of large models to smaller ones often by updating the latter's parameters, through teacher forc

APEX: Adaptive Expert Prefetching for Memory-Efficient Edge MoE Inference

arXiv:2608.11688v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models are attractive for edge deployment because they provide high model capacity while activating only a small subset of pa

researcharxiv-cs-ai

Convergent Detour Hijacking: Task-Preserving Resource Amplification in Skill-Based LLM Agents

arXiv:2608.12273v1 Announce Type: cross Abstract: LLM agents increasingly rely on third-party skills, using natural-language descriptions for selection and instruction bodies for planning. This progre

Diagnosis Before Recovery: Turning Agent Failures into Selective Self-Correction

arXiv:2608.11772v1 Announce Type: new Abstract: Self-correction is particularly useful when a failure constrains the next repair. Coding agents benefit from this property because compilers, tests, and

safetyarxiv-cs-cl

ExRole: From Team Trajectories to Executable Roles in Multi-Agent Language Models

arXiv:2608.11949v1 Announce Type: new Abstract: Roles provide an interpretable interface for organizing language-model agents, yet most multi-agent systems treat them as hand-written prompt labels dis

FM-LLM: A frequency-enhanced mixture-of-experts framework for adapting LLMs to time series forecasting

arXiv:2608.11623v1 Announce Type: cross Abstract: Recent advances in Large Language Models (LLMs) have spurred cross-modal solutions for time-series forecasting. However, existing methods rely heavily

Generation as Auxiliary Supervision: Enhancing Visual Understanding at Zero Inference Overhead via Decoupled Embedding Prediction

arXiv:2608.12209v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) have achieved remarkable progress, visual understanding and generation are typically treated as divergent

Local Ai

Map-Det3D: Metric Feed-Forward 3D Reconstruction Prior for Multi-view 3D Object Detection from Streaming Inputs

arXiv:2608.12179v1 Announce Type: new Abstract: Metric 3D object detection is a core capability for embodied agents, yet most reliable systems lean on depth sensors, trading away cost, power, and inte

local-aiarxiv-cs-cv

Applications

Poly-Dialectal Neural Machine Translation System for Bangla Regional Dialects

arXiv:2608.12018v1 Announce Type: new Abstract: Regional dialectal variation poses a fundamental challenge to natural language processing (NLP) in Bangla, where over 240 million speakers communicate a

applicationsarxiv-cs-cl

RECAST: A Machine-Learning Framework for Correction and Super-Resolution of Coarse-Grid PDE Solvers

model-releasesarxiv-cs-lg

arXiv:2608.11572v1 Announce Type: new Abstract: Coarse-grid numerical solvers can substantially reduce the computational cost of time-dependent PDE simulation, but under-resolution often degrades both

Self-Evolving Embodied Agents via Skill-Harness Evolution

model-releasesarxiv-cs-cl

arXiv:2608.11350v1 Announce Type: new Abstract: Embodied agents are increasingly built as systems around foundation models, where performance depends not only on model weights but also on the skills,

Tutorials

Self-Supervised Weighted Image Guided Quantitative MRI Super-Resolution

arXiv:2512.17612v2 Announce Type: replace Abstract: Object: To present and evaluate Self-supervised Weighted Image Guided quantitative MRI Super-Resolution (SWIG qMRI SR), a physics-informed framework

tutorialsarxiv-cs-cv

Towards foundation-style models for energy-frontier heterogeneous neutrino detectors via self-supervised pre-training

arXiv:2604.07037v2 Announce Type: replace-cross Abstract: Accelerator-based neutrino physics is entering an energy-frontier regime in which interactions reach the TeV scale and produce exceptionally d

Towards Tighter Convex Relaxation of Mixed-Integer Programs: Leveraging Logic Network Flow for Task and Motion Planning

arXiv:2509.24235v2 Announce Type: replace Abstract: This paper proposes an optimization-based task and motion planning framework, named 'Logic Network Flow,' that integrates temporal logic specificati

researcharxiv-cs-ro