All entries

Deep denoising autoencoder-based non-invasive blood flow detection for arteriovenous fistula

arXiv:2306.06865v2 Announce Type: replace-cross Abstract: Clinical guidelines underscore the importance of regularly monitoring and surveilling arteriovenous fistula (AVF) access in hemodialysis patie

Content type

All Blog X Post Paper YouTube Reddit GitHub

Deep Reinforcement Learning for Reach-Avoid-Stay Problems

DGX agent

arXiv:2410.02898v3 Announce Type: replace-cross Abstract: Reach-Avoid-Stay (RAS) tasks are essential in applications where systems must safely reach a target set and remain within it under all bounded

safetyarxiv-cs-lg

3 Sept 2026

DeepAffinity: Long-Term Aspect Preference Prediction in eCommerce using Small Language Models

arXiv:2609.02468v1 Announce Type: cross Abstract: We explore predicting eCommerce user preferences for product aspects such as brand, size, and color - a task we define as Aspect Affinity. Solving thi

Deeply Interleaved Text-Image Contexts for Multimodal LLMs Assessment

arXiv:2609.02573v1 Announce Type: new Abstract: Current evaluations and training of multimodal models predominantly focus on multi-image tasks, largely overlooking interleaved text-image scenarios. In

DeepSeek-V4-Flash vs. GLM-5.3-Flash on 2× DGX Spark

model-releasesr-localllama

I've tried both and been having this debate with myself for the last few days, on two Asus Ascent GX10s (effectively the same as 2x DGX Spark): DeepSeek-V4-Flash-0731 (official weights) GLM-5.3-Flash

Agents

Degeneracy-Resilient Teach and Repeat for Geometrically Challenging Environments Using FMCW Lidar

arXiv:2603.10248v2 Announce Type: replace Abstract: Teach and Repeat (T&R) topometric navigation enables robots to autonomously repeat previously traversed paths without relying on GPS, making it well

agentsarxiv-cs-ro

DESA-TTA: Dynamic EMA and Source Anchoring for Test-Time Adaptation

arXiv:2609.01795v1 Announce Type: new Abstract: Vision-language object detectors (VLODs) achieve strong zero-shot performance but remain vulnerable to distribution shifts during deployment. Mean-teach

Design and Validation of a Lightweight, Low-Profile Powered Knee Prosthesis with Quasi-Direct Drive Actuation

arXiv:2609.02003v1 Announce Type: new Abstract: Fully-powered knee prostheses, unlike traditional passive knees, can perform controlled positive work, reducing the need for compensatory behaviors by u

researcharxiv-cs-ro

Designing Versatile Samples for Learned Trajectory Scoring

arXiv:2609.01799v1 Announce Type: cross Abstract: Many current end-to-end driving policies emit a pool of candidate trajectories and select one, which makes selection a separable component: a scorer c

Detecting Object Hallucinations in Large Vision-Language Models via Cross-Modal Attention Drifts and Mask-Based Verification

arXiv:2609.02028v1 Announce Type: new Abstract: Despite recent advances in large vision-language models (LVLMs), object hallucination remains a major barrier to their reliable deployment. Existing det

Local Ai

Diagnosing with Insights: Structured Analysis of Agent Failures via Behavioral Abstractions

arXiv:2609.02371v1 Announce Type: new Abstract: With the proliferation of LLM agents, the ability to understand and diagnose failures in agents is essential to achieving superior effectiveness and tru

local-aiarxiv-cs-ai

Dictionary-Guided Mutation Operators for Automated HDL Repair

model-releasesarxiv-cs-ai

arXiv:2609.01775v1 Announce Type: cross Abstract: Automated repair of Hardware Description Language (HDL) designs remains challenging due to the large search space of candidate repairs and the strict

DiDrive: A Risk-Aware Hierarchical Diffusion Framework for Safe Offline Reinforcement Learning in Autonomous Driving

model-releasesarxiv-cs-lg

arXiv:2609.01609v1 Announce Type: new Abstract: While diffusion models effectively capture multimodal behavioral priors for autonomous driving, offline reinforcement learning (RL) policies remain susc

Tutorials

Differentiable Electricity-Market Clearing for Gradient-Based Planning

arXiv:2609.02646v1 Announce Type: new Abstract: Planning a large data center is difficult because a facility big enough to matter changes the electricity prices it will pay. Those prices are set by ma

tutorialsarxiv-cs-lg

DiffIE: Diffusion-based Open Information Extraction

arXiv:2609.02315v1 Announce Type: cross Abstract: A single sentence often expresses multiple valid relational triplets, which makes Open Information Extraction (OpenIE) fundamentally a multi-output ta

Local Ai

DiffuSearch: How Hybrid Trajectory Planning Benefits from Aligned Objectives in Diffusion and Action Space

arXiv:2609.02252v1 Announce Type: cross Abstract: In trajectory planning for autonomous driving, hybrid planning architectures are often realized as a collection of disparate modules, each with its ow

local-aiarxiv-cs-ai

Diffusion-Encoding Gaussian Field for Joint k-q dMRI Reconstruction

arXiv:2609.02288v1 Announce Type: new Abstract: Diffusion MRI requires repeated k-space acquisitions over multiple diffusion-encoding directions, making acquisition time dependent on both spatial and

Dimension Dependent Correlation Gap Bounds under Restricted Independence

arXiv:2609.02659v1 Announce Type: cross Abstract: The pairwise independent correlation gap is the ratio of the maximum expected value of a set function under arbitrary dependence to that under pairwis

researcharxiv-cs-lg

DiscoSign: Discourse-Aware Text to Sign Language Gloss Translation

arXiv:2609.02796v1 Announce Type: new Abstract: Sign language processing systems have traditionally operated at the sentence level, ignoring critical discourse phenomena fundamental to sign language c

researcharxiv-cs-cl

Discriminative World Models for Web Agents

model-releasesarxiv-cs-ai

arXiv:2609.02885v1 Announce Type: new Abstract: Recent web agents use world models for test-time action selection by sampling candidate actions, predicting the resulting web states, and ranking them w

Disease Burden over Skin Tone: Decomposing the Dermatology-AI Generalization Gap

arXiv:2609.02111v1 Announce Type: cross Abstract: Dermatology artificial intelligence (AI) models are predominantly trained on light-skinned, cancer-focused image collections, yet they are increasingl

Disentangling Statistical Preemption from Entrenchment in Language Models' Avoidance of Overgeneralization

arXiv:2609.01794v1 Announce Type: new Abstract: How do learners avoid overgeneralizations such as Tom laughed me without explicit negative evidence? Constructionists have posited two proposals that de

researcharxiv-cs-cl

Diversifying Long Prompt Image Generation through Structured Prompt Embedding Space Sampling

arXiv:2511.20251v2 Announce Type: replace Abstract: Modern text-to-image models produce impressive visual results from richly specified prompts, yet their behavior under long prompts remains insuffici

DKL: Decoupled Knowledge Learning for Instruction-Tuned Language Models

arXiv:2609.02685v1 Announce Type: cross Abstract: RAG has become the de facto method for incorporating new, corpus-specific knowledge into an instruction following LLM (Instruct LLM). Although RAG-bas

DLM-One: Diffusion Language Models for One-Step Sequence Generation

model-releasesarxiv-cs-cl

arXiv:2506.00290v2 Announce Type: replace Abstract: This paper introduces DLM-One, a score-distillation-based framework for one-step sequence generation with continuous diffusion language models (DLMs

DMRL: Document-Mediated Reinforcement Learning for Skill Optimization in Advertising Recommendation

arXiv:2609.02170v1 Announce Type: new Abstract: Advertising recommendation requires continuously tuning complex system parameters while balancing commercial returns and user experience. Recent work ha

safetyarxiv-cs-lg

Do Better Imagined Rollouts Mean Better Robot Control? A Controlled Study of World-Model Evaluation Under Feedback

arXiv:2609.02811v1 Announce Type: new Abstract: Predictive models are increasingly used in robotics for state estimation, planning, control, and policy evaluation, yet they are often judged by open-lo

safetyarxiv-cs-ro

Do Cantonese-Adapted Language Models Better Predict Cantonese Reading? A Cross-Model Eye-Tracking Evaluation

arXiv:2609.02163v1 Announce Type: new Abstract: Information-theoretic measures derived from autoregressive language models are widely used to characterize the expectations that shape human reading, bu

safetyarxiv-cs-cl

Do Large Language Models Always Tell The Same Stories?

arXiv:2606.17350v2 Announce Type: replace-cross Abstract: Recent advances in large language models (LLMs) have enabled the generation of high-quality prose, yet whether these models are capable of gen

Do Large Language Models Capture the Diversity in their Training Data?

arXiv:2609.02275v1 Announce Type: cross Abstract: Large language models are trained to model conditional distributions over text, yet it remains inadequately understood whether they capture the full d

Tutorials

Do Tabular Foundation Models Know Physics? Contamination, Units, and the Deterministic Limit

arXiv:2609.02766v1 Announce Type: new Abstract: Tabular foundation models (TFMs) learn to fill in tables the way language models fill in text, and tables are arguably the format in which most physical

tutorialsarxiv-cs-lg

DocHop: Benchmarking Out-of-domain Multi-hop Reasoning in Information-Dense Documents

model-releasesarxiv-cs-ai

arXiv:2609.02059v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have achieved strong performance on structured visual understanding tasks such as chart and document question a

Agents

Document extraction just got a new gear. ⚡️ Introducing Turbo mode for Extract, our fastest way yet to pull structured data from documents. …

Document extraction just got a new gear. ⚡️ Introducing Turbo mode for Extract, our fastest way yet to pull structured data from documents. It runs roughly 4× faster than our Cost Effective Tier at co

agentsjerry-liu--x

Does Playing it Safe Count as Faithfulness? Reassessing LVLM Hallucination Mitigation Methods

arXiv:2609.01888v1 Announce Type: new Abstract: Recent inference-time hallucination mitigation methods for large vision-language models (LVLMs) report strong gains on hallucination benchmarks. However

Domain shift-robust object detection with GenAI image editing

arXiv:2609.02299v1 Announce Type: new Abstract: Object detectors often degrade under domain shifts such as changes in lighting, weather, or occlusion. These shifts alter object appearance and expose a

Applications

Door-in-the-Face Requests and Refusal Behaviour in Large Language Models

arXiv:2609.02707v1 Announce Type: new Abstract: Does the door-in-the-face technique work on language models? In humans, a large request that is refused makes a smaller follow-up request more likely to

applicationsarxiv-cs-ai

Applications

Doppio: A Dataset for Contactless Weight Estimation of Falling Particles

arXiv:2609.02528v1 Announce Type: new Abstract: Measuring the mass of powder, including falling particles, is a common task in industrial applications. While scales are effective for static measuremen

applicationsarxiv-cs-cv

Double-Bounded Nonlinear Optimal Transport for Size Constrained Min Cut Clusterin

model-releasesarxiv-cs-lg

arXiv:2501.18143v2 Announce Type: replace Abstract: Min cut is an important graph partitioning method. However, current solutions to the min cut problem suffer from slow speeds, difficulty in solving,

Doubly Stochastic Adaptive Neighbors Clustering via the Marcus Mapping

arXiv:2408.02932v3 Announce Type: replace-cross Abstract: Clustering is a fundamental task in machine learning and data science, and similarity graph-based clustering is an important approach within t

DPA: Decoupling Product-Agnostic Anomaly Representations for Zero-shot Anomaly Generation

arXiv:2609.02075v1 Announce Type: new Abstract: Industrial anomaly detection benefits from anomaly samples, yet newly deployed products typically provide only normal images, making anomaly samples dif

Dutch Books for Language Models

arXiv:2609.02797v1 Announce Type: cross Abstract: People increasingly use language models to support life decisions. Many such decisions involve a probabilistic forecast: How likely is a major life ev

DWFF-Net: A Multi-Scale Farmland System Habitat Identification Method with Adaptive Dynamic Weight Feature Fusion

arXiv:2511.11659v3 Announce Type: replace Abstract: To address insufficient accuracy in multi-scale segmentation for agricultural habitat recognition, this study proposes a Dynamic Weighted Feature Fu

DynaTokens: Controlling Token Dynamics for Continual Video-Language Understanding

arXiv:2603.06662v3 Announce Type: replace Abstract: Continual VideoQA with multimodal LLMs remains challenging because sequential adaptation induces task interference, while storing task-specific prom

Local Ai

DynG-Diff: A State-Aware Dynamic Guidance Diffusion Framework for Probabilistic Time Series Forecasting

arXiv:2609.02068v1 Announce Type: new Abstract: Probabilistic multivariate time series (MTS) forecasting is crucial for modeling complex dynamical systems. However, existing diffusion-based methods re

local-aiarxiv-cs-lg

EarlyEval: Cheaper Agent Evaluation via Early Outcome Prediction

model-releasesarxiv-cs-cl

arXiv:2609.02783v1 Announce Type: new Abstract: Evaluating LLM agents is essential for guiding their development, yet it has grown prohibitively expensive: a single pass of a frontier model over an ag

Edit Knowledge, Not Just Facts via Multi-Step Reasoning over Background Stories

arXiv:2602.02028v3 Announce Type: replace Abstract: Enabling artificial intelligence systems, particularly large language models, to update knowledge and flexibly apply it during reasoning remains a c

Efficient All-in-One Weather Restoration using Spectral Harmonization

arXiv:2609.02839v1 Announce Type: new Abstract: Adverse weather conditions such as rain, haze, and snow significantly degrade image quality, posing challenges for both human perception and physical AI

Efficient Context-Limited Telescope Bibliography Classification for the WASP-2025 Shared Task Using SciBERT

arXiv:2609.01647v1 Announce Type: new Abstract: The creation of telescope bibliographies is a crucial part of assessing the scientific impact of observatories and ensuring reproducibility in astronomy

safetyarxiv-cs-lg