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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

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

DGX agent

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

model-releasesarxiv-cs-ai

25 Sept 2026

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

EndoFSA: Endoscopic Few-Shot Image Generation via Rank-Constrained Parameter Adaptation

model-releasesarxiv-cs-cv

arXiv:2609.29930v1 Announce Type: new Abstract: WCE produces large-scale gastrointestinal image data yet pathological findings remain significantly underrepresented limiting the generalization perform

ENDOPROMPT: Victim-Side Pseudo-References for Utility Degradation

arXiv:2609.29948v1 Announce Type: new Abstract: Prompt injection can degrade benign task performance without eliciting harmful content. Yet many attack objectives depend on task labels or predefined t