Search: “papers”

Programming and execution of skill-based human-robot-crane collaborative tasks

arXiv:2609.03392v1 Announce Type: new Abstract: Highly varying production sets increasing challenges for robotic manufacturing and indoor logistics. New capabilities for agility, flexibility, and robu

applicationsarxiv-cs-ro

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RACE-AIMC: Selective Inference for Heterogeneous Analog In-Memory Accelerators at the Edge

DGX agent

arXiv:2609.03149v1 Announce Type: cross Abstract: Analog in-memory computing (AIMC) speeds up neural-network inference by doing the arithmetic directly inside a memory array, instead of shuttling weig

researcharxiv-cs-lg

4 Sept 2026

Real-Time Shape Control of Multi-Segment Soft Robotic Arms Using Koopman Operators with Global and Local Observables

arXiv:2609.03175v1 Announce Type: new Abstract: Multi-segment soft robotic arms can continuously reconfigure their body shapes for safe interaction, but tip control alone is insufficient for constrain

researcharxiv-cs-ro

Agents

Risk and Anomaly Identification for Distribution Network Optimal Operation Based on Reinforcement Learning and Uncertainty Quantification

arXiv:2609.03308v1 Announce Type: new Abstract: Reliable operation of modern distribution networks requires timely identification of operational risks and anomalous events under pervasive uncertainty.

agentsarxiv-cs-lg

Agents

RoughSense: Lightweight Terrain-Induced Rover Vibration Prediction Using Point Clouds and IMU Feedback

arXiv:2609.03720v1 Announce Type: new Abstract: Autonomous navigation in space requires reliable terrain assessment for safe operations, especially in underground environments with limited communicati

agentsarxiv-cs-ro

ScoreMix: Synthetic Data Generation by Score Composition in Diffusion Models Improves Recognition

arXiv:2506.10226v3 Announce Type: replace-cross Abstract: Synthetic data generation is increasingly used in machine learning for training and data augmentation. Yet, current strategies often rely on e

Select, Compress, Reinvest: A Controlled Study of Visual-Token Allocation in Long-Video MLLMs

arXiv:2609.03820v1 Announce Type: cross Abstract: Long-video language models cannot look at every frame: an hour sampled once per second is 3,600 images, and a system keeps only a small fixed slice of

safetyarxiv-cs-cl

Sequential Beats Joint: On the Interplay between On-Policy Distillation and RLVR

arXiv:2609.04108v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) and on-policy distillation (OPD) have emerged as two dominant methods for post-training reasonin

Skyfall-GS: Synthesizing Immersive 3D Urban Scenes from Satellite Imagery

arXiv:2510.15869v4 Announce Type: replace Abstract: Synthesizing large-scale, explorable, and geometrically accurate 3D urban scenes is a challenging yet valuable task for immersive and embodied appli

applicationsarxiv-cs-cv

SpecAlign: Efficient Specification-Grounded Alignment of Large Language Models via Synthetic Data

arXiv:2606.16276v3 Announce Type: replace Abstract: As large language models (LLMs) are increasingly deployed in real-world applications, alignment is no longer governed by a single universal notion o

Stable and Scalable Bundle Adjustment of Holistic 3D Structures

arXiv:2609.04026v1 Announce Type: new Abstract: Bundle Adjustment (BA) is a cornerstone of 3D computer vision and has benefited from decades of advances in sparse optimization and numerical methods. I

applicationsarxiv-cs-cv

Subspace Inference Enables Efficient Active Reward Learning from Preferences

arXiv:2609.04066v1 Announce Type: cross Abstract: Reinforcement learning from human feedback (RLHF) has emerged as a powerful yet sample-inefficient approach for learning reward models from human pref

SurgeGen: A Hybrid Generative Diffusion Framework for Storm Surge Scenario Synthesis

arXiv:2609.03382v1 Announce Type: cross Abstract: Predicting storm surge induced by landfalling tropical cyclones is crucial for flood mitigation and coastal risk management. Traditionally, physics-ba

researcharxiv-cs-lg

Symmetries and Causality: Causal Effect Identification Beyond IID Data

arXiv:2609.03697v1 Announce Type: cross Abstract: In the natural sciences, symmetries and cause-effect relationships are ubiquitous. Yet for complex machine-learning tasks, like world-modeling in rein

TabScope: Question-Adaptive Scope Selection for Table Question Answering

arXiv:2609.03395v1 Announce Type: cross Abstract: Large Language Models (LLMs) have shown strong performance on table question answering, yet their accuracy often degrades as table size increases. We

The Natural Language Interaction Protocol and Standard for AI Agents

arXiv:2609.04135v1 Announce Type: new Abstract: AI agents are increasingly being developed and deployed across organizations using heterogeneous agent-development frameworks, AI models, tool interface

local-aiarxiv-cs-ai

To What Extent Do Large Language Models Understand Bangla Idioms?

arXiv:2609.03410v1 Announce Type: new Abstract: Idiomatic expressions are an integral part of natural language, reflecting cultural nuances and posing unique challenges for computational models, parti

Tutorials

TokenMatch: 3D Mesh Correspondence Transformer with Curvature-Guided Tokenisation

arXiv:2609.04202v1 Announce Type: new Abstract: While data-driven 3D shape correspondence estimation has recently seen substantial progress, robust matching under partial observations and strong non-i

tutorialsarxiv-cs-cv

Towards a Statistical Understanding of Mixture-of-Experts

arXiv:2609.03501v1 Announce Type: cross Abstract: Mixture-of-experts (MoE) architectures increase model capacity by combining a collection of expert predictors through input-dependent routing, while o

researcharxiv-cs-lg

Traceable TTS: Toward Watermark-Free TTS with Strong Traceability

arXiv:2507.03887v1 Announce Type: cross Abstract: Recent advances in Text-To-Speech (TTS) technology have enabled synthetic speech to mimic human voices with remarkable realism, raising significant se

TruncGradGS: Improved 3D Gaussian Splatting via Truncated Gradient Updates

arXiv:2609.03534v1 Announce Type: cross Abstract: 3D Gaussian Splatting has become a de facto scene representation for novel view synthesis, yet robustly learning 3D Gaussian primitives from visual in

Understanding Autonomous Driving Datasets by Describing Differences between Image Subsets in Natural Language

arXiv:2609.03677v1 Announce Type: cross Abstract: Understanding the composition of large-scale autonomous driving datasets is essential for safety, robustness, and reliable operation across domains. F

Value-Preserving Architectures for Agentic AI Systems

arXiv:2609.03920v1 Announce Type: new Abstract: The emergence of agentic AI and LLM-based multi-agent systems (MAS) presents unprecedented opportunities for automating complex tasks, while simultaneou

VestigeKV: The NoPE-MLA KV Cache Carries Its Own Eviction Signal in a Vestigial Branch

arXiv:2609.03949v1 Announce Type: cross Abstract: The problem. A long-lived KV cache must be compressed before the queries that will read it exist; selection by observed attention (H2O, SnapKV) collap

local-aiarxiv-cs-cl

Virtual Testing of Automated Driving Systems through Credible Simulations

arXiv:2609.03760v1 Announce Type: new Abstract: Simulation is increasingly used to support safety-related decision-making in road transport, particularly for the assessment and approval of automated d

safetyarxiv-cs-ro

Vision-Based Tactile Sensing for the Perception of the Object's Compliance and Hardness

arXiv:2510.12528v2 Announce Type: replace Abstract: Object compliance perception enables the identification of soft materials, supporting tasks such as fruit detection and assisted medical palpation.

researcharxiv-cs-ro

What Else Needs Fixing? Exploring Cost-Effective Test-Time Compute for Revision Propagation in Artifacts Generated Through Conversation

arXiv:2609.03254v1 Announce Type: new Abstract: Large Language Models (LLMs) often help users generate artifacts through iterative cycles of generation and revision in conversation. A challenge here i

Tutorials

Zero-Shot Novel Depth Synthesis Using 3D Foundation Models Scene Representations

arXiv:2609.04174v1 Announce Type: new Abstract: 3D Foundation Models (3DFMs) such as VGGT have recently pushed the boundaries of 3D vision by predicting rich unified representations with feed-foward t

tutorialsarxiv-cs-cv

A Survey of Transformer-based Language Models with Focus on Efficiency

arXiv:2406.16893v3 Announce Type: replace-cross Abstract: The emergence of Transformer-based Large Language Models (LLMs) has substantially augmented the capabilities of Natural Language Processing (N

A Top-Down Framework for Metric-Scale Athlete Localization from Single Broadcast Frames

arXiv:2609.02705v1 Announce Type: new Abstract: Accurate world-coordinate localization of athletes from single-frame broadcast footage is inherently challenging due to extreme scale disparities in ult

local-aiarxiv-cs-cv

A Tri-Agent Framework for Evaluating and Aligning Question Clarification Capabilities of Large Language Models

arXiv:2609.02054v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in interactive systems where understanding user intent precisely is paramount. A key capability f

A Unified Rate-Distortion Perspective on Vector, Product, and Scalar Quantization

arXiv:2609.02107v1 Announce Type: cross Abstract: Discrete visual tokenization, predominantly driven by vector, scalar, and product quantization, lacks a unified conceptual framework for understanding

safetyarxiv-cs-cv

Agents

Advancing Accessible Underwater Robotics: The Mini-Girona I-AUV at RAMI 2025

arXiv:2609.02605v1 Announce Type: new Abstract: The Mini-Girona Intervention Autonomous Underwater Vehicle (I-AUV) represents an advancement in accessible underwater robotics, designed to bridge the g

agentsarxiv-cs-ro

Backdoor Attacks on Speech Emotion Recognition via TTS-Generated Poisoning

arXiv:2606.21052v2 Announce Type: replace-cross Abstract: Speech Emotion Recognition (SER) systems increasingly leverage self-supervised acoustic representations, yet their vulnerability to training-t

CAHR-Net: Condition-Adaptive Hysteresis Reconstruction for Compact and Interpretable Magnetic Core Loss Modeling

arXiv:2609.01991v1 Announce Type: new Abstract: Magnetic core loss originates in the hysteresis loop: the energy dissipated per excitation cycle equals the loop area, and frequency, temperature, and w

researcharxiv-cs-lg

CARPAS: Towards Content-Aware Refinement of Provided Aspects for Summarization in Large Language Models

arXiv:2510.07177v2 Announce Type: replace Abstract: Aspect-based summarization has attracted significant attention for its ability to generate more fine-grained and user-aligned summaries. While most

applicationsarxiv-cs-cl

CC-4DGS: Computational Deformation and Point-Cloud Compression for Storage-Efficient Dynamic Gaussian Splatting

arXiv:2609.02184v1 Announce Type: new Abstract: Dynamic four-dimensional (4D) Gaussian Splatting has emerged as a powerful explicit representation for high-quality view synthesis, yet existing methods

researcharxiv-cs-cv

CoMerge: Conflict-Driven Preference Optimization for Multi-Task Model Merging

arXiv:2609.02273v1 Announce Type: new Abstract: Model merging provides an efficient paradigm for constructing multi-task large language models (LLMs) without full model retraining, yet it remains chal

Contrastive Explanations in Quantitative Bipolar Argumentation Frameworks

arXiv:2609.02399v1 Announce Type: new Abstract: Argumentation frameworks are useful tools for representing and reasoning with information in a variety of settings, e.g. in supplementing AI models as t

CrashDiffuser: VLM-Guided Collision Intent Reasoning for Fine-Grained Safety-Critical Traffic Scenario Generation

arXiv:2609.02270v1 Announce Type: cross Abstract: Generating safety-critical scenarios is essential for evaluating autonomous driving systems. However, existing generators primarily focus on inducing

Debias-SparseGPT: Bias-Aware Pruning for Large Language Models

arXiv:2609.02496v1 Announce Type: new Abstract: Model compression techniques such as pruning and quantization facilitate the efficient deployment and acceleration of Large Language Models (LLMs). Howe

safetyarxiv-cs-cl

Deep Reinforcement Learning for Reach-Avoid-Stay Problems

arXiv:2410.02898v3 Announce Type: replace-cross Abstract: Reach-Avoid-Stay (RAS) tasks are essential in applications where systems must safely reach a target set and remain within it under all bounded

safetyarxiv-cs-lg

Diagnosing with Insights: Structured Analysis of Agent Failures via Behavioral Abstractions

arXiv:2609.02371v1 Announce Type: new Abstract: With the proliferation of LLM agents, the ability to understand and diagnose failures in agents is essential to achieving superior effectiveness and tru

local-aiarxiv-cs-ai

Dictionary-Guided Mutation Operators for Automated HDL Repair

arXiv:2609.01775v1 Announce Type: cross Abstract: Automated repair of Hardware Description Language (HDL) designs remains challenging due to the large search space of candidate repairs and the strict

Diversifying Long Prompt Image Generation through Structured Prompt Embedding Space Sampling

model-releasesarxiv-cs-cv

arXiv:2511.20251v2 Announce Type: replace Abstract: Modern text-to-image models produce impressive visual results from richly specified prompts, yet their behavior under long prompts remains insuffici

Dutch Books for Language Models

arXiv:2609.02797v1 Announce Type: cross Abstract: People increasingly use language models to support life decisions. Many such decisions involve a probabilistic forecast: How likely is a major life ev

Efficient All-in-One Weather Restoration using Spectral Harmonization

arXiv:2609.02839v1 Announce Type: new Abstract: Adverse weather conditions such as rain, haze, and snow significantly degrade image quality, posing challenges for both human perception and physical AI

researcharxiv-cs-cv

Efficient Context-Limited Telescope Bibliography Classification for the WASP-2025 Shared Task Using SciBERT

arXiv:2609.01647v1 Announce Type: new Abstract: The creation of telescope bibliographies is a crucial part of assessing the scientific impact of observatories and ensuring reproducibility in astronomy

safetyarxiv-cs-lg