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Communication-Constrained Multi-Robot Exploration With Adaptive Communication Windows

arXiv:2609.12502v1 Announce Type: new Abstract: Exploring unknown environments with multi-robot teams can improve efficiency by allowing robots to explore in parallel. However, realizing these gains r

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Confidence-Gated Transductive Test Generation for Code Reranking

DGX agent

arXiv:2609.12489v1 Announce Type: cross Abstract: Test case synthesis is crucial for evaluating and ranking programs generated by large language models (LLMs). However, constructing high-quality test

researcharxiv-cs-cl

14 Sept 2026

Context-Aware Causal Gaze Forecasting for Human-Vehicle Interaction During In-Cabin Tracking Dropouts

arXiv:2609.12374v1 Announce Type: new Abstract: Dashboard-mounted gaze trackers often lose sight of the driver's eyes during large head rotations, including shoulder checks, mirror glances, and inters

Agents

Continue, Adapt, or Yield: In-Turn Adaptation to Overlapping Speech in Full-Duplex Agents

arXiv:2609.13117v1 Announce Type: new Abstract: Full-duplex evaluation often emphasizes whether an agent keeps speaking or stops. That binary cannot express a third response humans use routinely: cont

agentsarxiv-cs-cl

Control Architecture for Safe Grasping of Fragile Objects Using a Coarse Position-Controlled Gripper

arXiv:2609.12737v1 Announce Type: new Abstract: Robots are increasingly used in unstructured environments. The need for them to safely grasp unknown objects without damaging them becomes crucial. Huma

Convergence of Stochastic Gradient Methods under Heavy-Tailed Noise and Holder Smoothness

arXiv:2609.12785v1 Announce Type: new Abstract: Classical convergence guarantees for stochastic gradient methods typically assume Lipschitz-smooth objectives and finite-variance gradient noise, both f

CoralscapesV2: Panoptic and Fine-Grained Visual Scene Understanding in Coral Reefs

model-releasesarxiv-cs-cv

arXiv:2609.12826v1 Announce Type: new Abstract: In order to design conservation and restoration strategies to counter the global decline of coral reefs, ecological monitoring of reefs needs to be scal

Correlation-Guided Fast Machine Unlearning via Hessian Analysis

arXiv:2609.12620v1 Announce Type: new Abstract: The increasing adoption of machine learning in network and distributed security systems has created an urgent need for mechanisms that can selectively a

Cortex: Content Analysis Support Software, a Resource for Qualitative Research

arXiv:2609.11970v1 Announce Type: cross Abstract: Qualitative research is widely used in the human and social sciences, characterized by a deep understanding of phenomena through the interpretation of

researcharxiv-cs-cl

Creating an Atomic User Model for Personality-Aware Large Language Model Interaction

arXiv:2609.12086v1 Announce Type: cross Abstract: Assistants built on large language models are expected to write as their user would, and the dominant approach is single-channel: preferences summaris

researcharxiv-cs-cl

CRFCAN: A Complex-Valued Cross-Domain Residual Network for Joint Channel and Phase Noise Estimation in Sub-THz OFDM Systems

arXiv:2609.12244v1 Announce Type: new Abstract: In sub-terahertz (sub-THz) communications, the coupling of ultra-wide bandwidth and severe phase noise (PN) impairments renders conventional joint chann

CueMem: Cue-Guided Context Reconstruction for Long-Term Conversational Memory

arXiv:2609.12354v1 Announce Type: new Abstract: Long-term conversational agents must answer user queries by recalling information from extended dialogue histories, yet directly using the full history

researcharxiv-cs-cl

Curriculum-Based Adversarial Heterogeneous Agent Reinforcement Learning for Autonomous Quad-Copter Landing in Maritime Settings

arXiv:2609.12758v1 Announce Type: new Abstract: Recovering unmanned aerial vehicles (UAVs) in maritime environments is challenging due to wind turbulence and ship-deck motion, making it a valuable tes

DATAFARM: Distribution-Aligned Task and Motion Planning for Fine-Tuning Vision-Language-Action Models

arXiv:2609.12316v1 Announce Type: new Abstract: Collecting high-quality robot data remains a fundamental challenge for training robot foundation models. Task and motion planning (TAMP) offers a scalab

DCRA: Diffusion-Conditioned Representation Alignment for Robust Time-Series Learning

arXiv:2609.11997v1 Announce Type: new Abstract: Learning robust representations for time-series signals under noise and distribution shifts remains challenging, especially in clinical applications suc

safetyarxiv-cs-lg

Dead Weights, Live Signals: Feedforward Graphs of Frozen Language Models

arXiv:2604.08335v2 Announce Type: replace Abstract: We present a feedforward graph architecture in which heterogeneous frozen large language models serve as computational nodes, communicating through

Decentralized Evolution of Hexapod Gaits with Independent Leg Controllers

arXiv:2609.12400v1 Announce Type: cross Abstract: This paper presents a novel approach to hexapod locomotion by evolving each leg's gait independently through a decentralized evolutionary algorithm. U

Tutorials

Decoding Mixture Perception through Computational Modeling of Component Interactions

arXiv:2609.11958v1 Announce Type: new Abstract: Olfaction played an indispensable role throughout human evolution and civilization. Even in the contemporary era of advanced technology, olfaction remai

tutorialsarxiv-cs-lg

Decomposing Discrimination: Causal Mediation Analysis for AI-Driven Credit Decisions

arXiv:2603.27510v2 Announce Type: replace Abstract: Statistical fairness metrics in AI-driven credit decisions conflate two causally distinct mechanisms: discrimination operating directly from a prote

safetyarxiv-cs-lg

Tutorials

Deep learning methods for inverse problems using connections between proximal operators and Hamilton-Jacobi equations

arXiv:2512.23829v3 Announce Type: replace-cross Abstract: Inverse problems are important mathematical problems that seek to recover model parameters from noisy data. Since inverse problems are often i

tutorialsarxiv-cs-lg

DementiaCare-Bench: A Modality-Validated Video Benchmark

model-releasesarxiv-cs-cv

arXiv:2609.12929v1 Announce Type: new Abstract: Dementia affects an estimated 57 million people worldwide, and for most families the hardest part of care is not memory loss but the behavioral and psyc

Dense Dynamic Scene Reconstruction and Camera Pose Estimation from Multi-View Videos

arXiv:2603.12064v3 Announce Type: replace Abstract: We address the challenging problem of dense dynamic scene reconstruction and camera pose estimation from multiple freely moving cameras -- a setting

applicationsarxiv-cs-cv

DERA: Detached Edge-Residual Adaptation for Prohibited item Detection

arXiv:2609.12411v1 Announce Type: new Abstract: Prohibited-item detection in X-ray imagery remains challenging due to object superposition, weak texture, and material clutter which obscure both semant

Design, modelling and experimental validation of single and multisloped bipenniform architecture-based shape memory alloy-driven linear actuator

arXiv:2511.23372v2 Announce Type: replace Abstract: The increasing industrial demand for alternative actuators over conventional electromagnetism-based systems having limited efficiency, bulky size, c

applicationsarxiv-cs-ro

Detecting and Explaining Fake News Short Videos with Multimodal Content and Real-World Evidence

arXiv:2609.12678v1 Announce Type: new Abstract: Short-video platforms have become a primary news source for the public, which has also enabled the widespread dissemination of fake news videos. We stud

applicationsarxiv-cs-cv

DIA: Denoising Intermediate Advantage for Diffusion Policy Optimization

arXiv:2609.12245v1 Announce Type: new Abstract: Diffusion-based robot policies have become widely used in robotic manipulation, where they are typically trained with behavior cloning. However, policie

Tutorials

Diffusion Models and Concept Formation

arXiv:2609.13047v1 Announce Type: cross Abstract: Humans organize knowledge into a taxonomy of concepts with nested levels of abstraction and a basic level at which people recognize and name objects w

tutorialsarxiv-cs-lg

Dimension-Corrected Hitting Times for Heavy-Tailed Spectral Emergence in Neural Optimizer Dynamics

arXiv:2609.12994v1 Announce Type: new Abstract: Heavy-tailed empirical spectral densities of neural-network weight matrices are widely used as diagnostics of implicit self-regularization, but the step

Direct Topology Tracking in Continuous Implicit Models

arXiv:2609.12157v1 Announce Type: cross Abstract: We present a framework for tracking topological features directly within continuous implicit models. Such models, including implicit neural representa

Hardware

Dissecting GPU Utilization for LLM Inference on Nvidia Hopper

arXiv:2609.12923v1 Announce Type: cross Abstract: A single SM utilization percentage can make an LLM inference workload look compute-saturated while hiding how much useful work is being done. The prob

hardwarearxiv-cs-lg

Distortion of AI Alignment Revisited: RLHF is a Decent Utilitarian Aligner

arXiv:2609.12651v1 Announce Type: new Abstract: While Reinforcement Learning from Human Feedback (RLHF) is the standard paradigm for aligning large language models with human preferences, its effectiv

Distributed Stochastic Optimal Control for Pattern-Oriented Swarms

arXiv:2609.12959v1 Announce Type: new Abstract: While offering significant promise for diverse applications, pattern-oriented swarms encounter multifaceted challenges in geometric control, self-organi

Agents

Diverse Minds, Divided Networks? Personality Composition, Polarization, and Collective Intelligence in LLM-Based Social Simulations

arXiv:2609.12444v1 Announce Type: cross Abstract: Simulated societies of large language model agents are used to study online polarization, and separately to study collective intelligence, but the two

agentsarxiv-cs-cl

Do LLMs Trust the Accuser or the Accusation? Measuring Belief Shifts in Werewolf

model-releasesarxiv-cs-cl

arXiv:2609.12446v1 Announce Type: cross Abstract: Social-deduction games such as Werewolf are increasingly used to evaluate LLM agents, but existing evaluations often rely on final game outcomes. We p

Doc2FRC: Length-Consistent Document-Level Machine Translation via Fixed-Range Chunking

arXiv:2609.12674v1 Announce Type: new Abstract: Advanced large language models (LLMs) with long context windows can substantially reduce input truncation in document-level machine translation (DocMT).

safetyarxiv-cs-cl

Does Video Memory Use What It Retrieves? A Causal Audit of Memory Specificity

arXiv:2609.12090v1 Announce Type: new Abstract: Video models increasingly use memory to preserve information over long sequences, with the assumption that gains come from retrieving and using the corr

DRDN: Decoupled Representation Dynamic Network for From-Scratch ViT Class-Incremental Learning

arXiv:2607.01630v2 Announce Type: replace Abstract: Dynamic expansion methods for class-incremental learning (CIL) protect task-specific knowledge by growing dedicated tokens or subnetworks, yet our a

Agents

Driving Context-guided Model Predictive Planning and Control for Autonomous Car Racing at the Limit and Beyond

arXiv:2609.12660v1 Announce Type: new Abstract: This paper presents a Model Predictive Control-based motion planning and control pipeline for autonomous car racing capable of adapting to different dri

agentsarxiv-cs-ro

DropVLA: An Action-Level Backdoor Attack on Vision-Language-Action Models

arXiv:2510.10932v5 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models map multimodal perception and language instructions to executable robot actions, making them particularly

DRS-VPT: Directly Relocalizing in a Scan with Vision Point Transformers

arXiv:2609.12557v1 Announce Type: new Abstract: We present DRS-VPT, a feed-forward transformer architecture for foundational image-to-scan registration. Given query images and a reference 3D point clo

safetyarxiv-cs-cv

Hardware

Dual-guided Hierarchical Edge Localization for Large-scale Optimal Transport Across Dimensions

arXiv:2609.13010v1 Announce Type: new Abstract: Optimal transport (OT) compares distributions and aligns datasets in machine learning, yet unregularized discrete OT requires a linear program with quad

hardwarearxiv-cs-lg

Dual-Process Atomic Skill Learning: Decoupling Semantic Reasoning and Real-Time Control

arXiv:2607.10625v2 Announce Type: replace Abstract: Language-conditioned Imitation Learning (IL) is essential for enabling robots to perform complex tasks following natural language instructions. Howe

DuplexDrama: A Synthesized Dialogue Dataset with Scenarios, Full-Duplex Behaviors, Expressive Speech, and Sound Events

model-releasesarxiv-cs-cl

arXiv:2609.12872v1 Announce Type: new Abstract: We present DuplexDrama, the first synthesized spoken dialogue dataset that simultaneously covers four dimensions: (i) complete persona and scenario sett

DWMP: Leveraging Dual World Models for Humanoid Obstacle Traversal

arXiv:2609.12347v1 Announce Type: new Abstract: Humanoid robots must traverse cluttered obstacle fields using onboard proprioceptive and visual observations, yet existing methods usually process multi

Hardware

Dynamic Expert Quantization for Scalable Mixture-of-Experts Inference

arXiv:2511.15015v4 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) has become a practical architecture for scaling LLM capacity while keeping per-token compute modest, but deploying Mo

hardwarearxiv-cs-lg

Dynin-Robotics: Omnimodal Unified Diffusion Vision-Language-Action Model

arXiv:2609.13053v1 Announce Type: cross Abstract: Visual goal and dynamics prediction can provide language-conditioned robot policies with both a target outcome and a representation of action-dependen

safetyarxiv-cs-lg

DynSHAP: Towards Explainable Dynamic Survival Analysis

arXiv:2609.13042v1 Announce Type: new Abstract: Deep learning models for dynamic survival analysis (DSA) achieve strong predictive performance by incorporating longitudinal patient data, but their bla

applicationsarxiv-cs-lg

EAR: Entity-Aware Partitioning Approach for Retrieval-Augmented Generation Development

model-releasesarxiv-cs-cl

arXiv:2609.12268v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) can improve knowledge-intensive question answering, but the first design choice is easy to overlook: how should the