Search: “framework”

MICRO: Multi-Fidelity Active Search for Severe Error Discovery

arXiv:2609.26025v1 Announce Type: cross Abstract: Human feedback can vary in cost and informativeness. Strong feedback can reveal severe errors but is costly, so cheaper quality ratings can help decid

researcharxiv-cs-cl

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MirrorDistill: Illumination-Aware Latent Distillation for Efficient Low-Light Restoration

DGX agent

arXiv:2609.25331v1 Announce Type: new Abstract: Low-light image enhancement (LLIE) is an im- portant component of visual sensing systems operating under degraded illumination, including nighttime surv

safetyarxiv-cs-cv

23 Sept 2026

Mitigating LLM Over-Refusal via Dynamic Semantic Routing Calibratione

arXiv:2609.25049v1 Announce Type: new Abstract: Large language models (LLMs) aligned for safety often suffer from over-refusal, incorrectly rejecting benign yet safety-related instructions. Prior stud

local-aiarxiv-cs-cl

MorphoSHAP: Rethinking the Unit of Attribution in Explanation for Deep Visual Models

arXiv:2609.25815v1 Announce Type: new Abstract: Visual attribution methods typically explain predictions using pixels, superpixels, or regular patches. These representations can localize important reg

local-aiarxiv-cs-cv

MT-ProtBERT: Multi-task Learning ProtBERT for Intrinsically Disordered Proteins Classification with Scarce Data

arXiv:2609.25334v1 Announce Type: new Abstract: Intrinsically disordered proteins (IDPs) differ from folded proteins in that they are dynamic, lack a stable three-dimensional conformation, and have lo

Multi-Term Fourier Graph Neural Network with Sample Relationship Learning for Enhanced Remaining Useful Life Prediction

arXiv:2609.25179v1 Announce Type: new Abstract: Predicting the remaining useful life (RUL) is essential for effective predictive maintenance. Spatio-Temporal Graph Neural Networks (ST-GNNs), which can

Multi-View Fair Clustering Guided by Cross-View Sensitive Information Discrepancy

model-releasesarxiv-cs-lg

arXiv:2609.25811v1 Announce Type: new Abstract: Multi-view clustering (MVC) aims to uncover latent cluster structures by exploiting complementary information from multiple views. Despite substantial p

NaCR: Visual Localization via NeRF-aided Camera Ray Regression

arXiv:2609.25907v1 Announce Type: new Abstract: Visual localization (VL) is a fundamental technology for vision applications such as virtual reality. Recently, a novel VL paradigm, Camera Ray Regressi

local-aiarxiv-cs-cv

Observed Control - Linearly Scalable Nonlinear Model Predictive Control with Adaptive Horizons

arXiv:2508.13339v2 Announce Type: replace-cross Abstract: This work highlights the duality between state estimation and model predictive control. A model predictive controller, observed control, is pr

researcharxiv-cs-ro

On the Effect of Bit-Level Parameter Perturbations in Machine Learning and Deep Learning Models

model-releasesarxiv-cs-lg

arXiv:2609.26280v1 Announce Type: new Abstract: In this chapter, we investigate how classical machine learning models respond to small, targeted modifications in their parameters. We compare and contr

OptiSkill: A Hierarchical and Evolving SkillBank for LLM-Based Optimization Modeling

arXiv:2609.22987v1 Announce Type: new Abstract: Automated operations research (OR) modeling requires LLMs to translate natural-language decision problems into correct mathematical programs. Existing m

local-aiarxiv-cs-ai

PAKT: Physically-Aligned Kinesthetic Teaching for Reinforcement Learning

arXiv:2609.25630v1 Announce Type: new Abstract: Real-world reinforcement learning (RL) systems still struggle with the demands of contact-rich industrial manipulation, including micrometer-level preci

Physics-guided deep metric learning with continuous time embeddings for open-world radar pulse de-interleaving

arXiv:2609.25057v1 Announce Type: cross Abstract: Radar pulse de-interleaving is a foundational Electronic Support Measures (ESM) task that aims to separate chronologically interleaved pulse streams f

PhyVisGen: Physically and Visually High-Fidelity Robotic Manipulation Data Generation

arXiv:2609.25653v1 Announce Type: new Abstract: Large-scale manipulation demonstrations are essential for learning robust visuomotor policies, yet real-world data collection is expensive and difficult

PINNForge: Execution-Grounded Evolutionary Design of Physics-Informed Neural Networks for PDE Solving via Large Language Models

arXiv:2609.23023v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) require coordinated choices over network representation, sampling, loss construction, and optimization, while e

researcharxiv-cs-ai

PLAT: Sparse Timed Keyframe Motion Tracking for Humanoid Control via Privileged Latent Transition Learning

arXiv:2609.25754v1 Announce Type: new Abstract: Humanoid motion tracking policies rely on dense frame-by-frame references, limiting their use as high-level motion controllers for planning and interact

Polyak-Type Extragradient Methods for Monotone Root-Finding Problems

arXiv:2609.26581v1 Announce Type: cross Abstract: We study Polyak-type step-size selection for extragradient methods for solving deterministic and stochastic monotone root-finding problems. We show th

Pretraining of Medical Visual Encoders Toward Multi-modal Large Language Models

arXiv:2609.23860v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) commonly reuse visual encoders pretrained with CLIP, although the features of these ViTs are ultimately consume

local-aiarxiv-cs-ai

QuantWM: Temporally Consistent 2-Bit KV Cache Quantization for World Models and Video Generation

arXiv:2609.26425v2 Announce Type: new Abstract: KV cache memory has become a major deployment bottleneck for video generation and world models, which motivates low-bit quantization study for efficienc

Radiomics-Conditioned Modulation of RenalCLIP Features for Clear Cell Renal Cell Carcinoma Classification

arXiv:2609.26492v1 Announce Type: new Abstract: Radiomics provides quantitative descriptions of tumour appearance that may complement disease-specific foundation models in small labelled cohorts. We i

Real-Time Atomic-Resolution Electron Phase Imaging without Probe Calibration via Ptychography-Supervised Learning

arXiv:2609.25684v1 Announce Type: new Abstract: Atomic-scale phase imaging is central to resolving defects, interfaces, and weakly scattering atoms that govern the behavior of nanoscale materials. Ele

local-aiarxiv-cs-cv

ReasonLab: A Controlled and Auditable Evaluation of Prompting Techniques for Multiple-Choice QA

arXiv:2607.14109v2 Announce Type: replace Abstract: Probing the capabilities of Large Language Models (LLMs) and building robust solutions for Multiple-Choice Question Answering (MCQA) remain central

researcharxiv-cs-cl

RECAP: Relation Evidence Calibration for Detecting Spatial Relation Hallucinations in Vision-Language Models

arXiv:2609.26093v1 Announce Type: new Abstract: Vision-language models can answer spatial relation questions confidently even when the image supports an incompatible relation. We formulate relation-gr

REDACT: Robust Perceptive Locomotion under Unseen Visual Corruption

arXiv:2609.25450v1 Announce Type: new Abstract: Depth-conditioned locomotion policies have demonstrated impressive agile maneuvers, but can be steered to unpredictable actions when observations are ou

applicationsarxiv-cs-ro

Reinforcement Learning for Delivery Drone-Based Participatory Sensing in Dynamic Environments

arXiv:2607.18874v2 Announce Type: replace Abstract: Using Unmanned Aerial Vehicle (UAV) for urban sensing has emerged as a powerful paradigm to monitor the status of the city, e.g., air quality and no

applicationsarxiv-cs-lg

Relative Wasserstein Angle and the Problem of the W_2-Nearest Gaussian Distribution

arXiv:2601.22355v2 Announce Type: replace Abstract: Understanding the distributional structure of high-dimensional datasets has become an important topic, yet direct visual characterization is difficu

Riemannian Optimization on Tree Tensor Networks with Application in Machine Learning

model-releasesarxiv-cs-lg

arXiv:2507.21726v3 Announce Type: replace-cross Abstract: Tree tensor networks (TTNs) are widely used in low-rank approximation and quantum many-body simulation. In this work, we present a formal anal

ROAM-ASD: Robust Open-World Active Speaker Detection with Flexible Multimodal Fusion

arXiv:2609.26648v1 Announce Type: cross Abstract: Active speaker detection (ASD) requires reliable association between visible faces and acoustic speech, yet existing systems often degrade under chall

Robust Active-Perception Control for Global-State-Free Aerial-Ground Cooperation

arXiv:2609.25898v1 Announce Type: new Abstract: Aerial-ground cooperation requires real-time UAV--UGV relative-state information. Instead of maintaining global estimates for both robots, direct contro

local-aiarxiv-cs-ro

RouteRLT: Learning When and Which RL Specialist Should Control a Vision-Language-Action Policy

arXiv:2609.26467v1 Announce Type: new Abstract: Vision-language-action (VLA) models provide broad manipulation competence, but often struggle during the precision-critical stages that dominate contact

Safety-Constrained Model Predictive Control for an Omnidirectional Walking Assistive Robot Using Control Barrier Function

arXiv:2609.25994v1 Announce Type: new Abstract: Providing safe and effective mobility assistance plays a crucial role in restoring independence and enhancing the quality of life for individuals with m

SBMVTrack: Spike-Budgeted Multi-View Learning for Energy-Efficient UAV Tracking

model-releasesarxiv-cs-cv

arXiv:2609.25503v1 Announce Type: new Abstract: With sparse and event-driven computation, spiking neural networks show great potential for achieving accurate and energy-efficient UAV visual tracking.

Self-Supervised Combinatorial Optimization with Constraints via Frank-Wolfe

arXiv:2609.25728v1 Announce Type: new Abstract: Self-supervised learning for combinatorial optimization has emerged as a promising paradigm for solving discrete optimization problems with neural netwo

Semantic-Anchored Evidential Fusion for Domain-Robust Whole-Slide Survival Analysis

arXiv:2606.19966v2 Announce Type: replace-cross Abstract: Whole-slide images (WSIs) are widely used for computational cancer prognosis. However, most existing methods primarily focus on in-domain perf

Semantic Self-Distillation for Language Model Uncertainty

arXiv:2602.04577v3 Announce Type: replace Abstract: Large language models present challenges for principled uncertainty quantification, in part due to their complexity and the diversity of their outpu

researcharxiv-cs-cl

Shallow to Deep: Aligning Token Pruning with Stage-wise Roles in LVLMs

model-releasesarxiv-cs-cv

arXiv:2609.25635v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) incur high computational costs from redundant visual tokens. Although training-free attention-based multi-layer pru

Sonicmesh: Enhancing 3D Human Mesh Reconstruction in Vision-Impaired Environments With Acoustic Signals

arXiv:2412.11325v2 Announce Type: replace Abstract: 3D human mesh reconstruction (HMR) from RGB images often degrades under poor illumination, occlusion, and non-line-of-sight conditions. Acoustic sen

SPARC: SuperPixel-Aware Region Contrastive Learning for Self-Supervised Dense Prediction

arXiv:2609.25067v1 Announce Type: cross Abstract: Self-supervised learning (SSL) has become an effective approach for learning visual representations without manual annotations. Among SSL approaches,

Spatiotemporal Calibration of Doppler Velocity Logs for Underwater Robots

arXiv:2510.24571v2 Announce Type: replace Abstract: The calibration of extrinsic parameters and clock offsets between sensors for high-accuracy performance in underwater SLAM systems remains insuffici

applicationsarxiv-cs-ro

SpeakerMem-R1: Speaker-Centered Dual-Track Memory for Multi-Party Dialogue

arXiv:2609.26780v1 Announce Type: new Abstract: Long-term conversational memory in multi-party settings requires more than retrieving relevant content from long-term conversations: it must distinguish

local-aiarxiv-cs-cl

SPEANet: Structural Prior Enhanced Attention Network for Parameter-Efficient Remote Sensing Object Detection

model-releasesarxiv-cs-cv

arXiv:2609.26064v1 Announce Type: new Abstract: Remote sensing object detection (RSOD) requires compact backbones capable of preserving weak geometric cues under extreme scale variation and background

StrataVLA: Hierarchical and Efficient 3D Geometric Grounding for Vision-Language-Action Models

arXiv:2609.26071v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models inherit strong semantic priors from large-scale vision-language pretraining, yet remain limited in robotic manipulat

applicationsarxiv-cs-ro

StreamTTO: Efficient Online Test-Time Optimization for Video Depth Completion

arXiv:2603.01765v5 Announce Type: replace Abstract: Monocular depth foundation models generalize across diverse scenes, but recovering accurate metric depth consistent with a target sensor remains cha

SyzHarness: Patch-Based Kernel Bug Reproduction with LLM-Synthesized Fuzzing Harnesses

model-releasesarxiv-cs-ai

arXiv:2609.23889v1 Announce Type: cross Abstract: Automated kernel vulnerability reproduction is essential for bug triage, patch validation, and regression testing, but still lacks an effective and ef

TelecomGPT-R1: Unified Post-Training for Reasoning Across Heterogeneous Telecom Tasks

model-releasesarxiv-cs-cl

arXiv:2609.25356v1 Announce Type: new Abstract: Large language models (LLMs) offer great potential to automate a broad range of telecom engineering tasks by reasoning over standards, network configura

Tutorials

TEMPURA: Temporal Event Masked Prediction and Understanding for Reasoning in Action

arXiv:2505.01583v2 Announce Type: replace Abstract: Understanding causal event relationships and achieving fine-grained temporal grounding in videos remain challenging for vision-language models (VLMs

tutorialsarxiv-cs-cv

The Moral Check: Strategic AI Governance for the Pacing Problem

arXiv:2609.22869v1 Announce Type: cross Abstract: Technology cannot steer itself. Strategy provides that steering, establishing the rule that purpose and judgment must precede compute capital. As the

safetyarxiv-cs-ai

Toolcompass: Guiding Tool Trialing, Not Suppressing It

arXiv:2609.25678v1 Announce Type: cross Abstract: Large language model (LLM) agents must generalize from tools seen during training to unseen tools at deployment. A key challenge is tool trialing, i.e