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

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

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Downside-Controlled Online Forecast Combination under Delayed and Revised Outcomes

DGX agent

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

25 Sept 2026

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

Applications

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

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

researcharxiv-cs-ai

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

EnigmaForge: The Question Is Hidden in the Story

arXiv:2609.30144v1 Announce Type: new Abstract: Most benchmarks hand the model a question. EnigmaForge hands it a stack of old documents and no question at all. Buried in the letters, receipts, and lo

EnSiTa - A Trilingual Multi-Domain Parallel Dataset and Benchmark for Domain-Specific Machine Translation

model-releasesarxiv-cs-cl

arXiv:2609.29511v1 Announce Type: new Abstract: Machine Translation (MT) for low-resource languages remains far behind that of high-resource languages, and the gap is widest in specialised domains, wh

Epistemic-Probabilistic Model for Guarded Multi-Agent LLM Coordination

arXiv:2609.29366v1 Announce Type: new Abstract: Multi-agent large language models (LLMs) have become ubiquitous in applied AI, yet their theoretical foundations remain surprisingly understudied. Viewe

Era by Eon: Benchmarking Enterprise Agents on Hidden Knowledge

arXiv:2609.30055v1 Announce Type: cross Abstract: In the Era by Eon benchmark, each question states the rules for its answer, and code computes the answer from a generated company's data. When agents

ERRAND: Budgeted Maintenance of Agent Memory

arXiv:2609.29545v1 Announce Type: new Abstract: Deployed agents run on handed-over knowledge: a frozen policy consults a briefing of consolidated items written before the stream begins. The world then

safetyarxiv-cs-ai

Error- and Prediction-Driven Motor Learning in the Cortico-Cerebellar Loop

arXiv:2609.29945v1 Announce Type: new Abstract: Robust control under delayed sensory feedback remains a key challenge in both robotics and neuroscience. Classical cerebellar models explain delay compe

Evaluating Cross-region Generalization for Wavelet-Diffusion Precipitation Downscaling

arXiv:2609.28749v1 Announce Type: new Abstract: Diffusion models have shown strong potential for kilometer-scale precipitation downscaling, but their performance in geographically unseen regions and e

Evaluating Explanation-Driven Vision-Language Reasoning via Generation Order Interventions

arXiv:2609.29496v1 Announce Type: new Abstract: Natural language explanation generation serves as a key mechanism for exposing and evaluating vision-language reasoning. Prior work on explanation-drive

researcharxiv-cs-cl

Evaluation of Multi-Turn Consistency in LLM Agents: Survival Analysis and Failure-Rationale Taxonomy

arXiv:2609.29508v1 Announce Type: new Abstract: Large language model (LLM) agents may perform well on isolated tasks yet drift into inconsistency over extended interaction. We evaluate temporal consis

safetyarxiv-cs-ai

Evaluation of OpenAI o1: Opportunities and Challenges of AGI

arXiv:2409.18486v5 Announce Type: replace Abstract: This comprehensive study evaluates the performance of OpenAI's o1-preview large language model across a diverse array of complex reasoning tasks, sp

tutorialsarxiv-cs-cl

Evidence-Driven Differential Diagnosis of Malignant Melanoma

arXiv:2609.29613v1 Announce Type: cross Abstract: We present a modular and multi-level framework for the differential diagnosis of malignant melanoma. Our framework integrates contextual information a

researcharxiv-cs-ai

EvoTreeNAD: Genealogy-Guided Evolution for LLM-Driven Neural Architecture Discovery

arXiv:2609.29016v1 Announce Type: cross Abstract: AI-driven scientific discovery accelerates research by autonomously developing solutions and designs. Large language model (LLM) agents support this p

agentsarxiv-cs-lg

Exact Bayes Regret and Asymptotic Optimality in High-Dimensional Gaussian Bandits

arXiv:2609.28718v1 Announce Type: cross Abstract: We study Bayesian linear bandits with an isotropic Gaussian parameter, independent Gaussian candidate arms, and Gaussian reward noise when the horizon

Exploiting answer-invariant redundancies in satellite imagery for efficient VLM inference on edge

arXiv:2609.29029v1 Announce Type: new Abstract: Onboard vision-language models could enable satellites to answer queries directly, but exhaustive tiled inference over high-resolution imagery is slow a

researcharxiv-cs-cv

Exploiting Target Knowledge from MLLMs for Robust Few-Shot Segmentation

model-releasesarxiv-cs-cv

arXiv:2609.28949v1 Announce Type: new Abstract: Few-shot segmentation (FSS) aims to segment unseen object categories with a few (e.g., one or five) labeled examples, enabling efficient adaptation to n

ExplorationBench: Measuring AI Systems' Exploration in Verifiable Alien Worlds

arXiv:2609.30199v1 Announce Type: new Abstract: Scientific discovery begins where known problems end. There, AI systems must engage in exploration: framing hypotheses, designing experiments, and itera

fable.intermittent: benchmarking probabilistic forecasting methods for intermittent time series

arXiv:2609.28607v1 Announce Type: new Abstract: Intermittent time series are common in spare-parts demand and retail sales. Since the cost of forecast errors is typically asymmetric, decisions such as

Fair Like Us? Auditing LLM Alignment in Resource Allocation

arXiv:2609.29692v1 Announce Type: new Abstract: Fair allocation of scarce, indivisible resources is an important challenge in many societal problems. While there are several formal theories of fairnes

safetyarxiv-cs-ai

Faster Visuomotor Policy Learning on Action Manifolds via Riemannian MeanFlow

arXiv:2609.30127v1 Announce Type: new Abstract: Visuomotor policies learn a direct map from raw sensory observations to robot action sequences. Policies based on Diffusion and Flow Matching capture th

safetyarxiv-cs-ro

FB-GDM: Fully-Bayesian Guided Diffusion Models for High-Dimensional Linear Inverse Problems via Unsupervised Variational Inference

arXiv:2609.29216v1 Announce Type: cross Abstract: Diffusion models are powerful priors for linear inverse problems, but the reference guidance methods, Diffusion Posterior Sampling (DPS) and Pseudoinv

researcharxiv-cs-ai

Feature Space Selection and Heterogeneous Effect Estimation for Blood-Brain Barrier Permeability: A Random Forest to the Generalized Random Forest Pipeline

arXiv:2609.29076v1 Announce Type: cross Abstract: Predicting blood-brain barrier (BBB) permeability is critical for central nervous system drug discovery. Using the MoleculeNet BBBP dataset (n = 2039)

Federated Learning of AnDE Classifiers

arXiv:2609.28695v1 Announce Type: new Abstract: This work presents a federated framework for training Averaged n-Dependence Estimators (AnDE) in distributed environments. The proposed method focuses o

Applications

Few-Shot Specific Emitter Identification via Integrated Complex Variational Mode Decomposition and Spatial Attention Transfer

arXiv:2512.16786v2 Announce Type: replace-cross Abstract: Specific emitter identification (SEI) utilizes passive hardware characteristics to authenticate transmitters, providing a robust physical-laye

applicationsarxiv-cs-lg

FlashLoop: Fast and Memory-Efficient Looped Transformers via Lazy Updates

arXiv:2609.29812v1 Announce Type: new Abstract: Looped Transformers have attracted substantial attention as a parameter-efficient approach to increasing computational depth through repeated applicatio

FlowAtom: Atom-Based Evidence Aggregation for Multi-Label Website Fingerprinting

arXiv:2609.29330v1 Announce Type: new Abstract: Identifying the set of monitored websites in mixed encrypted traffic is challenging because an individual flow often provides only partial evidence of w

FluidRain: Incompressible Rain Flow as an Attention Bias for Loop-in-Loop Video Deraining

arXiv:2609.29006v1 Announce Type: new Abstract: Existing video deraining methods typically exploit neighboring frames through either explicit alignment or implicit spatiotemporal aggregation. Explicit

safetyarxiv-cs-cv

Fly, Drive, Reconfigure: A Modular Reconfigurable Aerial-Ground Platform for Field Operations

arXiv:2609.28887v1 Announce Type: new Abstract: Heterogeneous robot teams distribute complementary capabilities across specialized agents, but their physical roles and capacities typically remain fixe

agentsarxiv-cs-ro