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arXiv:2610.06087v1 Announce Type: new Abstract: Game-theoretic attribution explains a model by assigning credit to its features or training examples. The least core has attracted interest as an altern

hardwarearxiv-cs-lg

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Rethinking Long-Video Efficiency: A Joint Allocation Perspective on Frames, Pixels, and Front-End Latency

DGX agent

arXiv:2610.04318v1 Announce Type: new Abstract: Efficient long-video understanding with vision-language models (VLMs) is often framed as selecting informative frames or visual tokens at a fixed native

researcharxiv-cs-cv

6 Oct 2026

Rethinking Self-Distillation for Multi-Teacher Capability Merging

arXiv:2610.04272v1 Announce Type: new Abstract: Combining capabilities of multiple expert models trained starting from the same base checkpoint has become increasingly common in frontier language-mode

safetyarxiv-cs-lg

Hardware

Rethinking Streaming-Perception Evaluation on Heterogeneous Edge Platforms

arXiv:2610.05578v1 Announce Type: cross Abstract: Multi-camera streaming perception is increasingly deployed on heterogeneous edge platforms shared with co-resident workloads, yet accelerator placemen

hardwarearxiv-cs-cv

Rethinking Tabular Foundation Models On Data Streams

arXiv:2610.05352v1 Announce Type: new Abstract: Tabular foundation models (TFMs) outperform established machine learning models on tabular benchmarks through in-context learning. Building on this succ

Retrieval-Based In-Context Learning: A Domain Adaptation Framework

arXiv:2610.05717v1 Announce Type: cross Abstract: In-context retrieval (ICR) is a retrieval-based form of in-context learning (ICL) in which demonstrations are retrieved from a source database based o

Retrieval-Centric Deep Learning in Growing Nonparametric Neural Networks

arXiv:2610.03858v1 Announce Type: new Abstract: We investigate a general-purpose layer for deep learning that, instead of compressing arbitrary-size training data into fixed-size weight matrices, stor

Return-to-Home Feasible Micro-Aerial Vehicle Exploration for 3D Gaussian Splatting Reconstruction

arXiv:2610.04013v1 Announce Type: new Abstract: Micro aerial vehicles (MAVs) enable rapid indoor 3D reconstruction for inspection and time-critical situational awareness, but must operate under strict

Revealing After Overwriting: An Exponential POMDP OPE Lower Bound under History-Dependent Logging

arXiv:2610.05063v1 Announce Type: new Abstract: Multi-step revealing can make off-policy evaluation tractable under memoryless logging. With history-dependent logging, state decodability and target-re

safetyarxiv-cs-lg

Revisiting Ground-Truth Synthesis from High-Speed Video: Exact Validity Conditions and an Audited Consumer Capture Corpus

arXiv:2610.05298v1 Announce Type: new Abstract: Motion-deblurring datasets are commonly synthesised by averaging N consecutive high-frame-rate frames and labelling the result with the central frame. W

Revisiting Label-Free Speaker Embedding Enhancement with vMF Profile Likelihood

arXiv:2610.06691v1 Announce Type: cross Abstract: Embedding enhancement improves speaker verification under acoustic mismatch without modifying a frozen backbone. Recent work has established a practic

Revisiting the Broken Symmetry Phase of Solid Hydrogen: A Neural Network Variational Monte Carlo Study

arXiv:2512.17703v3 Announce Type: replace-cross Abstract: The crystal structure of high-pressure solid hydrogen remains a fundamental open problem. Although the research frontier has mostly shifted to

Revisiting the Generalization of Neural Graph Edit Distance Models

arXiv:2610.04644v1 Announce Type: new Abstract: Neural approaches to Graph Edit Distance (GED) have achieved strong results under standard within-dataset evaluation, but much less is known about how w

Reward-DAgger: Robot-Gated Interactive Imitation Learning with General-Purpose Progress-Based Reward Models

arXiv:2610.04054v1 Announce Type: new Abstract: Recent advances in robot learning have enabled generalist control policies capable of completing a wide range of tasks. However, their performance degra

RFG: Self-Improving Diffusion Large Language Models with Reward-Free Guidance

arXiv:2509.25604v2 Announce Type: replace-cross Abstract: Diffusion Large Language Models (dLLMs) have shown strong reasoning capabilities, yet further improving them typically requires costly post-tr

safetyarxiv-cs-lg

Riemannian Shape Analysis of the Corpus Callosum in Kendall Space: Aging and Alzheimer's Disease

arXiv:2610.05326v1 Announce Type: new Abstract: The corpus callosum (CC) is a major white-matter structure and a well-established marker of brain aging, but most studies quantify it using scalar summa

Applications

RiskFly: Frustum-Aligned Spatio-Temporal Risk Fields for One-Stage Agile Flight in Dynamic Clutter

arXiv:2610.04566v1 Announce Type: new Abstract: Agile flight in unknown, cluttered, and dynamic environments requires a planner that knows where and when danger will appear, not only that a trajectory

applicationsarxiv-cs-ro

RMMBench: A Comprehensive Benchmark for Robotic Mobile Manipulation

model-releasesarxiv-cs-ro

arXiv:2610.05414v1 Announce Type: new Abstract: Although the advancement of vision-language models (VLMs) has endowed robots with enhanced environmental understanding and task reasoning, a comprehensi

RoboIRS: Inference-Time Internal Representation Steering for Generalist Robot Policies

arXiv:2610.04681v1 Announce Type: new Abstract: Vision-language-action (VLA) and world-action models (WAMs) often degrade under out-of-distribution task variations despite retaining partial task capab

Robot Learning with Visual Predicted Force

arXiv:2610.04741v1 Announce Type: new Abstract: Force-aware manipulation typically relies on specialized force or tactile sensors. We show that force-aware manipulation can instead be achieved through

Robotic Long-Horizon Manipulation with Bayesian Non-parametric Skill Priors

arXiv:2503.21975v2 Announce Type: replace Abstract: Long-horizon manipulation under sparse rewards remains challenging for reinforcement learning due to delayed feedback and inefficient exploration. E

researcharxiv-cs-ro

Tutorials

Robotic Long-Horizon Manipulation with Progressive In-Context Code Generation and Episodic Feedback

arXiv:2503.21969v4 Announce Type: replace Abstract: Robotic long-horizon manipulation requires robots to compose perception, reasoning, and action over extended task sequences, yet existing language-c

tutorialsarxiv-cs-ro

Robotizing Human Videos with Physically Consistent Interactions

arXiv:2610.06137v1 Announce Type: new Abstract: Human videos offer scalable manipulation data, but the embodiment gap between human hands and robot manipulators limits their direct use. Existing video

Agents

RobotUse: Allocating Computation, Context, and Decisions

arXiv:2610.04929v1 Announce Type: new Abstract: Robot agents must connect their intended actions to observed outcomes while retaining the context needed to revise their choices over repeated attempts.

agentsarxiv-cs-ro

Robust 2D Traversability Mapping for Construction AMRs via Failure-Mode-Aware Fusion of LiDAR Geometry and Monocular Semantics

arXiv:2610.05505v1 Announce Type: cross Abstract: Autonomous Mobile Robots (AMRs) on active construction sites face severe navigational challenges: geometry-based traversability mapping (e.g., LiDAR)

safetyarxiv-cs-cv

Robust blind unmixing: A geometric approach to overcoming basis variation

arXiv:2610.04091v1 Announce Type: new Abstract: Signal separation problems are common in science. A prominent example of this occurs during the use of diffraction or spectroscopy to identify the indiv

Robust Ensemble Guidance for Scientific Inverse Problems

arXiv:2610.05371v1 Announce Type: new Abstract: Ensemble guidance combines pretrained diffusion priors with black-box forward models to solve inverse problems without differentiating through the physi

local-aiarxiv-cs-lg

Robust Local Optimization Done Right

arXiv:2610.05743v1 Announce Type: new Abstract: RANSAC scoring and local optimization (LO) impose different robustness requirements, motivating the separation of hypothesis selection from refinement.

local-aiarxiv-cs-cv

Robust Parameter-Efficient LLM Adaptation on Analog Hardware

arXiv:2610.05318v1 Announce Type: new Abstract: Analog in-memory computing is a promising platform for on-device execution of large language models because it performs matrix--vector multiplications (

Robust Surgical Robotic Instrument Tracking via Sequential Multi-Cue Fusion and Sim-to-Real Self-Training

arXiv:2610.05491v1 Announce Type: cross Abstract: Efficient and robust tracking of surgical robotic instruments is important for robot-assisted minimally invasive surgery, yet remains challenging due

Robust Tensor Completion via Reflective Convolution Nuclear Norm Minimization

arXiv:2610.04979v1 Announce Type: new Abstract: Robust tensor completion recovers multidimensional data from partial observations corrupted by sparse gross errors. Existing convolutional low-rank mode

RoMod: Temporal Routing Modulation via Mixture-of-Experts for Video Anomaly Detection

arXiv:2610.05131v1 Announce Type: new Abstract: Intermediate-layer features from multimodal large language models have shown strong potential for video anomaly detection (VAD), yet the origin of their

ROOT: Discovering Rewards for User-Specified Embodied Behaviors

arXiv:2610.04250v1 Announce Type: new Abstract: Reinforcement learning for embodied control remains constrained by the difficulty of reward specification. Although recent large language model (LLM)-ba

RoSA: Rotational Sparse Adaptation for Memory-Efficient Fine-Tuning

arXiv:2610.06243v1 Announce Type: new Abstract: Parameter-efficient fine-tuning (PEFT) reduces the cost of adapting foundation models by focusing training on a small parameter subset. Complementary to

ROT: Rotating Hidden States towards Contextual Vectors for Hallucination Mitigation in LVLMs

arXiv:2610.06056v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) frequently suffer from object hallucination. Existing training-free interventions primarily manipulate attention we

local-aiarxiv-cs-cv

Rotated, but How Far? Diagnosing and Improving Object-Rotation Reasoning in VLMs

arXiv:2610.05715v1 Announce Type: new Abstract: Vision-language models (VLMs) can detect that an object has rotated across views, but cannot reliably tell by how much. We introduce OR-Bench, a fine-gr

Round-Trip KNN Clustering: multiscale hierarchical cluster detection on directed nearest-neighbour graphs

arXiv:2610.06795v1 Announce Type: new Abstract: We introduce Round-Trip KNN Clustering (RTKNNC), a graph-based method for finding cluster structure at several neighbourhood scales without requiring th

Routing-Aware Safety Alignment for Mixture-of-Experts Models

arXiv:2602.04448v3 Announce Type: replace Abstract: Mixture-of-Experts (MoE) language models introduce unique challenges for safety alignment due to their sparse routing mechanisms, which can enable d

RPFQ-ViT: Rotated Phase-Frame Quantization for Extremely Low-Bit Weights in Vision Transformers

arXiv:2610.04457v1 Announce Type: new Abstract: Vision Transformers (ViTs) achieve strong performance on image recognition and mobile vision applications, but their high-dimensional linear projections

local-aiarxiv-cs-cv

RSure-Agent: Reliable Use of Tool Observations for Remote Sensing Agents

arXiv:2610.04836v1 Announce Type: new Abstract: Remote sensing agents rely on perception, measurement, and raster analysis tools to solve Earth observation tasks. We refer to their judgments and quant

S2PD: Serial-to-Parallel Diffusion for Physically and Logically Consistent Video Generation

arXiv:2610.06847v1 Announce Type: new Abstract: Bidirectional video diffusion models denoise entire videos in parallel, yet when trained on effectively unlimited in-distribution data from procedural g

Tutorials

S^3N: A Spherical Spiral Scanning Network for Weather Forecasting

arXiv:2610.04338v1 Announce Type: new Abstract: Machine learning-based weather prediction (MLWP) has achieved strong performance in global weather forecasting. Recent Hierarchical Equal Area isoLatitu

tutorialsarxiv-cs-lg

Safe Ergodic Control for Multi-Robot Systems via Quadratic Programming

arXiv:2610.05258v1 Announce Type: new Abstract: Ergodic control drives robots to spend time in each region in proportion to a spatial distribution of interest, making it well suited for dense spatiote

Safe Image Generation via Reinforcement Learning

arXiv:2610.05908v1 Announce Type: new Abstract: Recent Text-to-Image (T2I) models achieve remarkable visual image generation performance, but they can still generate NSFW (Not-Safe-For-Work) contents,

SALUS: Automated Auditing of NL-to-SQL Benchmarks through Weak Supervision of Multi-Agent Output

arXiv:2610.05540v1 Announce Type: cross Abstract: Natural language to SQL (NL-to-SQL) benchmarks are foundational to progress in data analysis research, yet recent work has shown that widely-used benc

Salvation Lies Within: Eliciting Inherent Style Transfer in Step-Distilled Diffusion Models

arXiv:2610.05066v1 Announce Type: new Abstract: Adapting step-distilled text-to-image (T2I) models through post-training incurs additional computational costs and affects native few-step generation be

Same Output, Different Gold: Measuring How Reference Choice Moves a Multilingual Benchmark Score

arXiv:2610.03825v1 Announce Type: cross Abstract: A benchmark score compares a system output against a reference, and methodological attention falls almost entirely on the first term. We measure the s

Same Pieces, Different Servers: A Tetris Benchmark for AI Agents as Served

arXiv:2603.02348v2 Announce Type: replace Abstract: An agent meets a model as served: through an endpoint with a price card, a shared cache and other tenants, or on whatever hardware a self-hosted mod