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Decoding Imagined Speech: A Strictly Subject-Independent Approach Using EEG

arXiv:2609.29820v1 Announce Type: new Abstract: Imagined speech decoding from electroencephalography (EEG) has gained increasing attention as a potential communication pathway for individuals with sev

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Decoupled Early Exits for Task-Dependent Compute Allocation in Flow-Matching VLAs

DGX agent

arXiv:2609.29382v1 Announce Type: cross Abstract: Flow-matching Vision-Language-Action (VLA) models have emerged as a potential solution for generalist robot control, designed by combining a pretraine

safetyarxiv-cs-lg

25 Sept 2026

Decoupled Learning and Selection in Slate Recommendation for Privacy and Stability Under Noisy Scores

arXiv:2609.29453v1 Announce Type: new Abstract: We formalize slate recommendation as a randomized score learner followed by deterministic selection. First, an appropriately scoped differential-privacy

researcharxiv-cs-lg

Decoupling Knowledge and Privacy: Post-Task Self-Distillation Replay for LLM Continual Learning

arXiv:2609.29711v1 Announce Type: cross Abstract: Privacy-preserving continual learning (PPCL) must reduce the reproduction of sensitive content while retaining useful knowledge across sequential task

Deep learning of longitudinal visual fields predicts glaucoma progression rate and identifies fast progressors

arXiv:2609.29256v1 Announce Type: cross Abstract: Glaucoma is the leading cause of irreversible blindness, and timely identification of fast progressors is essential to prevent disability. Current pra

Deep Positive-Unlabeled Anomaly Detection for Contaminated Unlabeled Data

arXiv:2405.18929v3 Announce Type: replace-cross Abstract: Semi-supervised anomaly detection, which aims to improve the anomaly detection performance by using a small amount of labeled anomaly data in

DEEPO: Dual-Entropy Enhanced Policy Optimization for Hallucination in MLLMs

arXiv:2609.28570v1 Announce Type: new Abstract: Reinforcement learning (RL) is widely used to sharpen reasoning in multimodal large language models (MLLMs), yet its effect on hallucination is uneven.

Delay-of-Gratification as a Multi-Agent Survival Micro-benchmark for Long-Horizon LLMs: Social Exposure, Personas, and Tool Use Budgets

arXiv:2609.29509v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as multi-turn agents that must sustain goals, use tools, and adapt to other agents over extended

DeltaWAM: Delta World Action Models for Bimanual Manipulation

arXiv:2609.28811v1 Announce Type: new Abstract: World-action models (WAMs) transfer visual and motion priors from pretrained video generators to robot control by jointly modeling visual dynamics and a

applicationsarxiv-cs-cv

Dense Coverage, Sparse Refinement: Byte-Constrained Cooperative Perception

arXiv:2609.29456v1 Announce Type: new Abstract: Collaborative perception improves autonomous perception by sharing intermediate Bird's-Eye-View (BEV) features across connected agents, but dense featur

agentsarxiv-cs-cv

Dense-Joint-Based Obstacle-Aided Locomotion with a Joint-Repositionable Snake Robot

arXiv:2609.29261v1 Announce Type: new Abstract: Obstacle-aided locomotion is a fundamental capability for snake robots to traverse complex environments. However, conventional rigid-link snake robots o

researcharxiv-cs-ro

Deploying real-time personalized speech with Qwen3-TTS on Amazon SageMaker AI

Deploy the publicly available Qwen3-TTS-12Hz-1.7B-Base text-to-speech model from Amazon SageMaker JumpStart to a fully managed, real-time endpoint, and clone a voice from a short reference clip. Cross

applicationsaws-ml-blog

Design and Evaluation of LLM Chaining-Based Task Planning for General Purpose Service Robots

arXiv:2609.29043v1 Announce Type: cross Abstract: General Purpose Service Robot (GPSR) tasks, as defined in the RoboCup@Home benchmark, require robots to interpret diverse natural language commands an

Detecting Data Poisoning in Code Generation LLMs via Black-Box, Vulnerability-Oriented Scanning

arXiv:2603.17174v2 Announce Type: replace-cross Abstract: Code generation large language models (LLMs) are increasingly integrated into modern software development workflows. Recent work has shown tha

applicationsarxiv-cs-ai

Detecting Glaucoma Across Multi-ethnic Myopic and Non-Myopic Populations Using an Uncertainty-Aware Vision Transformer: A Multicentre Model Development and Validation Study

arXiv:2609.29433v1 Announce Type: cross Abstract: Background: Artificial intelligence (AI)-based glaucoma detection from colour fundus photographs (CFP) offers scalable screening, but performance may

Did anyone do a full bench of e.g. Qwen Flash Next IQ4 and Qwen 27b FP8? Here are some

model-releasesr-localllama

edit: had to change formatting as I’m on mobile noe and the table broke.. I let Codex do a quick eval on Qwen 3.8 Flash Next IQ4_XS (served via vLLM + r9v) and Qwen 3.8 27B FP8 (served via vLLM + Radi

Diffusion-aided Task-oriented Semantic Communications with Model Inversion Attack

arXiv:2506.19886v3 Announce Type: replace-cross Abstract: Semantic communication enhances transmission efficiency by conveying semantic information rather than raw input symbol sequences. Task-oriente

researcharxiv-cs-lg

Direct Message Approximation (DMA): A Consistency-Based Framework for Tractable Approximate Inference on Factor Graphs

arXiv:2609.29466v1 Announce Type: cross Abstract: Approximate message passing on factor graphs underlies two dominant families of probabilistic inference algorithms: expectation propagation (EP) and v

tutorialsarxiv-cs-ai

Direction-Scale Decomposition in Action Representation: Rethinking What to Tokenize for Vision-Language-Action Models

arXiv:2609.28865v1 Announce Type: new Abstract: Action representation plays a central role in discrete-token vision-language-action (VLA) learning but remains underexamined. Under conventional pose-in

applicationsarxiv-cs-cv

DiscoPhon: Benchmarking the Unsupervised Discovery of Phoneme Inventories With Discrete Speech Units

model-releasesarxiv-cs-cl

arXiv:2603.18612v2 Announce Type: replace Abstract: We introduce DiscoPhon, a multilingual benchmark for evaluating unsupervised phoneme discovery from discrete speech units. DiscoPhon covers 6 dev an

Diverse Geometries, Frozen Weights: Robust Heterogeneous Treatment-Effect Estimation via Causal Expert Ensembles

model-releasesarxiv-cs-lg

arXiv:2609.29974v1 Announce Type: new Abstract: Estimating heterogeneous treatment effects from observational data is difficult because the most appropriate inductive bias varies with overlap, treatme

Do Audio Language Models Hear and Read Distinctive Features Alike?

arXiv:2609.30167v1 Announce Type: new Abstract: Audio language models pass speech and text through a single decoder. We ask whether that decoder represents a distinctive feature in the same direction

researcharxiv-cs-cl

Do World Models Make Better Robots? A Survey of Evaluation Benchmarks for Predictive Embodied Intelligence

arXiv:2609.29669v1 Announce Type: cross Abstract: Robot learning now advances along two tracks that rarely meet. On one side, direct Vision-Language-Action (VLA) policies map observations to actions a

safetyarxiv-cs-ai

DocuTeam: Mixed-Initiative Multi-Agent Discussions around Evolving Documents

arXiv:2609.29309v1 Announce Type: cross Abstract: In open-ended problem solving, collaborators often rely on discussion to surface concerns, challenge perspectives, and refine shared work as it evolve

Does a model's stated reason for rejecting a candidate do any work?

arXiv:2609.30151v1 Announce Type: cross Abstract: Asked to choose between candidates and explain the choice, a language model often rejects a rival by naming a fact its profile lacks: no director, no

Does DCGAN-Based Synthetic Augmentation Improve Brain Tumor MRI Classification? An Empirical Study

arXiv:2609.28508v1 Announce Type: cross Abstract: Generative adversarial networks (GANs) are increasingly used to augment medical imaging datasets, but synthetic images do not necessarily provide down

researcharxiv-cs-cv

Local Ai

Does per-frame early exit pay? A compute-matched study of dynamic depth for on-device speech enhancement

arXiv:2609.29867v1 Announce Type: cross Abstract: Deep learning-based speech enhancement is increasingly deployed on-device in hearing aids, headsets, and earbuds. Most of these devices, however, can

local-aiarxiv-cs-lg

Domain Recentering and Confidence-Weighted Prior Calibration for Vision-Language Models

arXiv:2609.29358v1 Announce Type: cross Abstract: Vision-language models such as CLIP achieve strong zero-shot classification, yet under distribution shift, visual embeddings drift from fixed text emb

safetyarxiv-cs-ai

DON’T LET YOUR CODING AGENT BE THE ONLY REVIEWER OF ITS OWN CODE. I’m seeing this in my own Claude / Codex sessions, and customers are sendi…

model-releasesitamar-friedman--x

DON’T LET YOUR CODING AGENT BE THE ONLY REVIEWER OF ITS OWN CODE. I’m seeing this in my own Claude / Codex sessions, and customers are sending me similar screenshots: | Qodo review is on the money. |

Don't Read the Log: Execution Traces Contaminate Verifiers in Video-Generation Agents

model-releasesarxiv-cs-lg

arXiv:2609.28564v1 Announce Type: cross Abstract: Agentic video-generation systems close a loop between a generator and a verifier: an LLM plans shots, calls a text-to-video model, and a multimodal ju

Downside-Controlled Online Forecast Combination under Delayed and Revised Outcomes

arXiv:2609.29096v1 Announce Type: new Abstract: Post-hoc correction adjusts a forecaster that cannot be retrained, such as a foundation model, but a correction fitted where errors are stable can hurt

safetyarxiv-cs-lg

DP-IPI: A Hybrid Differential Privacy Text Rewriting Mechanism for Indirect Personal Identifiers in Clinical Texts

arXiv:2609.29684v1 Announce Type: new Abstract: Despite the strengths of modern anonymization and de-identification techniques, the risk of re-identification remains significant due to the indirect id

researcharxiv-cs-cl

DrGait: Biomechanically Grounded Visual Reasoning for Interpretable Clinical Gait Analysis

arXiv:2609.28796v1 Announce Type: cross Abstract: Current automated gait analysis for clinical applications relies on uninterpretable black-box classifiers. Although Vision-Language Models (VLMs) offe

Driving Epidemic Models with AI Agents: the Epydemix Agent Framework

arXiv:2609.28692v1 Announce Type: new Abstract: Artificial Intelligence agents based on large language models provide convenient natural language interfaces to scientific software, but reliability is

Dual-Frontier: When Can an Agent Trust Its World Model?

arXiv:2609.26293v2 Announce Type: replace Abstract: Learned world models are becoming essential to general-purpose agents: by predicting action consequences, they support planning and decision-making

EAGER: Enhancing Generative Event Extraction via Reinforcement Learning with Verifiable Rewards

model-releasesarxiv-cs-cl

arXiv:2609.29230v1 Announce Type: new Abstract: End-to-end event extraction remains challenging for large language models as it requires simultaneous identification of event triggers, classification o

Echo in the Steps: Learning Perceptive Humanoid Parkour with Gated Memory

arXiv:2609.28960v1 Announce Type: new Abstract: While recent advances in perceptive locomotion have enabled humanoid robots to traverse structured terrains, agile parkour in highly discontinuous envir

applicationsarxiv-cs-ro

Local Ai

Edge AI on Constrained Devices for Binary Sleep-Wake Classification in Dynamic Environments

arXiv:2609.29163v1 Announce Type: new Abstract: This paper presents an Edge AI-based system for detecting sleep and wake states in non-stationary mobile environments using resource-constrained embedde

local-aiarxiv-cs-lg

Local Ai

Efficient Continuous DEM Reconstruction under Limited Target-Resolution Supervision

arXiv:2609.29864v1 Announce Type: new Abstract: High-resolution digital elevation models (DEMs) support Earth observation applications, but paired training references are often available only at coars

local-aiarxiv-cs-cv

Ego-Exo4D Human Meshes Dataset: 4D Human Motion Reconstruction for Ego-Exo Captures

arXiv:2609.30187v1 Announce Type: new Abstract: Ego-Exo4D is a large-scale dataset providing synchronized egocentric and multi-view exocentric video, a rich resource for skill learning and assessment,

researcharxiv-cs-cv

EgoSpeedUp: Transferring Human Manipulation Tempo to Robot Policies

arXiv:2609.29310v1 Announce Type: cross Abstract: Robot manipulation policies trained through imitation learning inherit not only the demonstrated behavior but also the conservative execution tempo of

tutorialsarxiv-cs-cv

EIB-Net: Entropy-Guided Information Bottleneck for Generalizable AI-Generated Image Detection

arXiv:2609.29064v1 Announce Type: cross Abstract: The proliferation of photorealistic AI-generated images demands robust detection methods that generalize across diverse generative models. While exist

tutorialsarxiv-cs-ai

ELF-REG: Scaling Continuous Diffusion Language Models to Reasoning Tasks

arXiv:2609.29102v1 Announce Type: new Abstract: Fully continuous diffusion language models (dLMs) denoise continuous representations without intermediate discretization, then decode all response token

safetyarxiv-cs-cl

ELiSe: Efficient Learning of Sequences in Structured Recurrent Networks

arXiv:2402.16763v3 Announce Type: replace-cross Abstract: Behavior can be described as a temporal sequence of actions driven by neural activity. To learn complex sequential patterns in neural networks

tutorialsarxiv-cs-ai

Elucidating the Conformal Structure of the Brinkman Penalisation Method for Geometry-Adapted, Structure-Preserving Operator Learning of Hamiltonian PDEs

arXiv:2609.29847v1 Announce Type: cross Abstract: The Brinkman penalisation method embeds boundary-value problems on complex domains into a simple computational box by modeling the solid region as a s

researcharxiv-cs-lg

Empath: Tracing Multi-Level Emotion Dynamics in Crisis Counseling Dialogues

arXiv:2609.29056v1 Announce Type: cross Abstract: Emotion dynamics are critical for understanding crisis-support conversations, yet most computational work treats emotion as static utterance-level lab

Enabling Approximate Joint Sampling in Diffusion LMs

arXiv:2509.22738v3 Announce Type: replace Abstract: In autoregressive language models, each token is sampled by conditioning on all the past tokens; the overall string has thus been sampled from the c

researcharxiv-cs-cl

Encoded but Not Decoded: Layer-Localized Evidence for a Three-Level Gap in LLM Syntax

model-releasesarxiv-cs-cl

arXiv:2609.29848v1 Announce Type: new Abstract: A language model can fail a syntactic test in two distinct ways: by not encoding the relevant structure, or by encoding it but failing to use it at the