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CALOS: Control-Affine Lyapunov On-manifold Safety Layer for Safe Deep Reinforcement Learning for Quadrotors

arXiv:2609.17758v1 Announce Type: cross Abstract: Deep Reinforcement Learning has demonstrated remarkable capability in quadrotor control, yet learned policies offer no guarantee of respecting safety

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Safety

Can MiniMax-H3 Reason About the Physical World? An Evaluation of Omni-Modal Generative Model

DGX agent

arXiv:2609.18323v1 Announce Type: new Abstract: Recent Omni-Modal Generative Models (Omni-Models) have advanced content generation toward unified modeling of text, images, video, and audio. MiniMax-H3

safetyarxiv-cs-cv

17 Sept 2026

Can VLMs Reliably Assess Sidewalk Accessibility Attributes from Pedestrian-Level Imagery?

arXiv:2609.17882v1 Announce Type: cross Abstract: An important component of urban accessibility, particularly for wheelchair users and people with reduced mobility, is sidewalk compliance with measura

CANTABILE: Learning Expressive Dynamics for Robotic Piano Performance

model-releasesarxiv-cs-ro

arXiv:2609.18213v1 Announce Type: new Abstract: Robotic piano playing has emerged as a standard benchmark for dexterous bimanual manipulation, yet progress on it has been measured almost entirely by n

Capability Emergence Can Be Forecast: Per-Seed, In Advance, With Calibrated Intervals, Certified False Alarms, and a Blind Pre-Registered Gate

arXiv:2609.19000v1 Announce Type: new Abstract: Emergent capabilities are widely treated as unpredictable: loss improves smoothly while abilities appear abruptly. Prior work offers early-warning indic

Hardware

CapMap-MS-TTA: 3rd Place Solution for the MUMU Track of the 8th LSVOS Challenge at ECCV 2026

arXiv:2609.18206v1 Announce Type: cross Abstract: The MUMU track of the 8th Large-scale Video Object Segmentation (LSVOS) Challenge requires a single unified multimodal model to jointly solve image ta

hardwarearxiv-cs-ai

CapMem: A Benchmark for Caption-Based Episodic Memory in Egocentric Video

arXiv:2609.17688v1 Announce Type: new Abstract: Wearable assistants require episodic memory over egocentric video, yet current vision-language models face bounded frame budgets, growing visual-token c

CARA: Collision-Aware Resolution Adaptation for Multiresolution Hash Encoding Based Image Fitting

model-releasesarxiv-cs-cv

arXiv:2609.18554v1 Announce Type: new Abstract: Multiresolution hash encodings have recently enabled fast and high-fidelity implicit neural representations by storing multi-scale features in fixed-siz

CaSCo: Cascade-Aware Soft-Collision Motion Planning

arXiv:2609.18910v1 Announce Type: new Abstract: Conventional motion planning treats collision as a binary constraint, although contact with different objects can have drastically different consequence

researcharxiv-cs-ro

Category Level 6D Object Pose Estimation from a Single RGB Image using Diffusion

model-releasesarxiv-cs-cv

arXiv:2412.11420v2 Announce Type: replace Abstract: Estimating the 6D pose and 3D size of an object from visual data is a fundamental task in computer vision. Although single-view geometry is a deeply

Applications

Causal-History Test-Time Scaling for Failure Recovery in Autoregressive World-Action Models

arXiv:2609.18016v1 Announce Type: new Abstract: World-action models (WAMs) have emerged as a promising paradigm for robot manipulation by jointly modeling future visual dynamics and robot actions. How

applicationsarxiv-cs-ro

CERA-MoA: Co-Evolving Routing Mechanisms with Continually Learning LLM Agents

arXiv:2609.18779v1 Announce Type: new Abstract: Current Mixture-of-Agents (MoA) paradigms generally treat query routing and agent fine-tuning as separate processes, limiting their ability to respond t

Changepoint-Aware World Models: Detecting Dynamics Shifts and Recovering by Forgetting Stale Replay in Model-Based RL

arXiv:2609.18950v1 Announce Type: new Abstract: A robot's learned model of its own dynamics is only valid until those dynamics change: actuators wear, payloads shift, and joints stiffen. A model-based

agentsarxiv-cs-lg

Characterizing Refraction-Induced Ranging Bias in Underwater Collaborative Localization

arXiv:2609.18073v1 Announce Type: new Abstract: This work studies how refraction-induced bias on acoustic ranging affects multi-agent collaborative localization in a range of oceanographic conditions

safetyarxiv-cs-ro

Characterizing Replay Retention Under Dynamics Shift in Model-Based Reinforcement Learning

model-releasesarxiv-cs-lg

arXiv:2609.18167v1 Announce Type: cross Abstract: Adapting to changes in robot dynamics requires learning from new data without discarding experience that may still be useful. In continual model-based

CLASP: A Cluster-Level Autonomous Selective Picking Robot with a Soft Rolling-Band Gripper for Fresh-Market Blueberry Harvesting

arXiv:2609.18051v1 Announce Type: new Abstract: Fresh-market blueberries require selective, gentle picking, which is labor-intensive and expensive. Over-the-row machine harvesters are fast but non-sel

agentsarxiv-cs-ro

Clueing up LLMs with Tool-Augmented Deductive Reasoning

arXiv:2609.18736v1 Announce Type: new Abstract: Despite recent advances in large language models (LLMs), performing logically consistent deductive reasoning over extended interactions remains challeng

CoAtNet-DeepMoE: A Convolution-Attention Hybrid with DeepSeek Mixture-of-Experts for Parameter-Efficient Tomato Disease Classification

model-releasesarxiv-cs-cv

arXiv:2609.18038v1 Announce Type: new Abstract: The world population is growing rapidly, and technology is improving in parallel. Meeting the huge demand for food for these 7 billion people not only d

Code Consistency Preference Optimization Verification for Language Model Alignment

model-releasesarxiv-cs-cl

arXiv:2609.19002v1 Announce Type: cross Abstract: Execution-based verification enhances large language models' mathematical reasoning through computational soundness and dependency-aware filtering. Ho

Cognitive Extensions for Dual-Process Language Agents: Memory and Self-Reflection in Interactive Environments

arXiv:2609.19128v1 Announce Type: new Abstract: Language agents remain brittle in interactive environments, where success requires long-horizon state tracking, valid action execution, and recovery fro

Colla-Q: Toward Collaborative Experts in MoE Quantization via Minimax Precision Balancing

arXiv:2609.18131v1 Announce Type: cross Abstract: In this paper, we present a Mixture-of-Experts (MoE) quantization method based on activation entropy. Although quantization reduces memory and computa

researcharxiv-cs-cl

Collaborative Memory for Multi-Agent VLM Systems

arXiv:2609.17921v1 Announce Type: new Abstract: Vision-language model (VLM) agents combine specialized perception, tools, and reasoning to address complex visual tasks. In multi-agent settings, differ

Collective Loss of Control in LLM Agent Systems: An Epidemic Account of Mutation, Contagion, and Recovery

arXiv:2609.18460v1 Announce Type: new Abstract: How does a multi-agent system evolve from a local deviation into collective loss of control? We propose an epidemic explanation organized around acciden

CompArt: Operationalizing Aesthetic Alignment in Text-to-Image Generation via Principles of Art

arXiv:2503.12018v2 Announce Type: replace-cross Abstract: Text-to-Image (T2I) diffusion models have made rapid progress on semantic alignment (generating what is described in the prompt), yet users st

COMPASS-ABS: Reducing Fragmentation in Shared GPU Clusters for Deep Learning Training Workloads

arXiv:2609.18519v1 Announce Type: cross Abstract: With the rapid advancement of deep learning technology, shared GPU clusters receive an increasing number of deep learning training (DLT) jobs. Yet res

safetyarxiv-cs-lg

Compiled Agency: Frontier General-Purpose Coding Agents Build Winning Game Players from Bare Interaction - from Flappy Bird to StarCraft II and Civilization

arXiv:2609.18996v1 Announce Type: new Abstract: LLM agents have repeatedly struggled to convert knowledge of a game into competent play, even when researchers build the agent around the model - supply

CompileRover: Revolutionizing Virtual Machine Compiler Optimization with a Tri-Role LLM-Driven Framework

arXiv:2609.19004v1 Announce Type: cross Abstract: Code optimization plays a crucial role in the development of virtual machine compilers, with optimization frameworks significantly enhancing the perfo

researcharxiv-cs-cl

Composite-Gradient Learning for Shared Control Authority Between Deep Reinforcement Learning and Model Predictive Control

arXiv:2609.17697v1 Announce Type: new Abstract: Integrated deep reinforcement learning (DRL) and model predictive control (MPC) methods are increasingly used to control autonomous systems by combining

agentsarxiv-cs-lg

Compositional Policy Violations: When Step-Level Compliance Fails In Agentic AI Workflows

arXiv:2609.18820v1 Announce Type: new Abstract: Agentic workflows now make consequential decisions in regulated settings, and the governance placed around them is almost entirely step-scoped: input-ou

Comprehensive reconstruction of collider events with hypergraph representation learning and graph-conditioned diffusion

arXiv:2609.18928v1 Announce Type: cross Abstract: In particle collider experiments, event reconstruction is the task of inferring the kinematics of short-lived particles produced in the hard scatter f

Local Ai

Compressive sensing inspired self-supervised single-pixel imaging

arXiv:2603.29732v2 Announce Type: replace Abstract: Single-pixel imaging (SPI) is a promising imaging modality with distinctive advantages in strongly perturbed environments. Existing SPI methods lack

local-aiarxiv-cs-cv

Confidence Comes from Experience: Experiential Confidence Estimation from Reasoning to Agents

arXiv:2609.17708v1 Announce Type: cross Abstract: Reliable confidence estimation is increasingly central to the trustworthy deployment of language models: a calibrated estimate of the probability that

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies

arXiv:2506.24048v2 Announce Type: replace-cross Abstract: Consensus-based optimization (CBO) has established itself as an efficient gradient-free optimization scheme, with attractive mathematical prop

Constrained PSLQ Search for Machin-like Identities Achieving Record-Low Lehmer Measures

arXiv:2508.08307v2 Announce Type: replace-cross Abstract: Machin-like arctangent relations are classical tools for computing pi, with efficiency quantified by the Lehmer measure (lambda). We present a

researcharxiv-cs-ai

Contiguity, Not Importance: Budgeted Repair of Stale KV Caches After Document Edits

arXiv:2609.17983v1 Announce Type: new Abstract: KV-cache reuse can reduce inference cost in retrieval-augmented generation and agentic systems, but cached contexts may become stale when retrieved know

Copy What Is Seen, Generate What Is Not: Training-Free Anomaly-Aware Video Restoration

arXiv:2609.18836v1 Announce Type: new Abstract: A surveillance system that detects an anomaly often has to repair the footage as well, yet the two tasks are studied in isolation: training-free anomaly

researcharxiv-cs-cv

CoRe-MARL: Cooperative Redistribution Under Unknown Dynamics Using Recurrent Multi-Agent Reinforcement Learning

arXiv:2609.18639v1 Announce Type: cross Abstract: Emergency management assistance programs, such as relief distribution, are essential for delivering necessary supplies to affected communities. Howeve

Correcting Boundary Bias and Observation Independence in Bayesian Experimental Design

arXiv:2602.01898v2 Announce Type: replace Abstract: In many experimental settings, active learning can improve sample efficiency by sequentially selecting where to measure, which is particularly valua

safetyarxiv-cs-lg

Correlation-Guided Encoder Selection for Multi-Encoder Large Audio-Language Models

model-releasesarxiv-cs-cl

arXiv:2609.18041v1 Announce Type: cross Abstract: Multi-encoder fusion extends Large Audio-Language Models (LALMs) beyond speech-centric recognition, but selecting encoders via intuition or exhaustive

CPR: Combining global composing, local performing and full-sequence refining in piano rendering with continuous autoregressive modelling

arXiv:2609.18216v1 Announce Type: cross Abstract: Prompt-conditioned piano MIDI-to-Music rendering aims to faithfully render target notes while reproducing the timbre of a reference recording. Existin

CSWAM: Better Causal Semantic Representations for Out-of-Distribution Generalization in World Action Models

arXiv:2609.18462v1 Announce Type: cross Abstract: FastWAM-style world action models enable efficient action-only inference, but generalize poorly under visual distribution shifts. Their reconstruction

researcharxiv-cs-ai

Cultural Competence in Context: A Large Language Model Passes the Turing Test in Finland

arXiv:2609.18394v1 Announce Type: new Abstract: We report the results of a Turing Test conducted in Finland in the Finnish language. Because languages and cultural contexts are unevenly represented in

researcharxiv-cs-ai

Curvature-aware Expected Free Energy as an Acquisition Function for Bayesian Optimization

model-releasesarxiv-cs-lg

arXiv:2603.26339v2 Announce Type: replace Abstract: We propose an Expected Free Energy-based acquisition function for Bayesian optimization to solve the joint learning and optimization problem, i.e.,

CzechTopic: A Benchmark for Zero-Shot Topic Localization in Historical Czech Documents

arXiv:2603.03884v2 Announce Type: replace-cross Abstract: Topic localization aims to identify spans of text that express a given topic defined by a name and description. To study this task, we introdu

DANTINOX: A Unified Framework for Multi-Paradigm Language Modeling

arXiv:2609.17535v1 Announce Type: new Abstract: Language generation research increasingly spans three paradigms: autoregressive decoding, discrete masked diffusion, and continuous flow-matching. Compa

researcharxiv-cs-cl

Dataset-Dependent Effects of Cross-Depth Aggregation and Soft-Routed Experts in EEG Foundation Model Fine-Tuning

arXiv:2609.17886v1 Announce Type: new Abstract: EEG decoding tasks can rely on different temporal dynamics and cross-channel relationships. We test whether specialized modules improve a fully fine-tun

Decentralized Optimal Equilibrium Learning Over Dynamic Networks

arXiv:2609.17601v1 Announce Type: cross Abstract: This paper studies decentralized learning of socially optimal equilibria in finite normal-form games over dynamic communication networks. Each agent o

Decodability is Not Causality: Dissociating Probe Readouts from Behavioral Drivers via SAE Decomposition

arXiv:2609.18080v1 Announce Type: new Abstract: Linear probes can decode safety-relevant concepts such as truthfulness from language-model activations, but probe accuracy may show only decodability, n