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arXiv:2604.17184v1 Announce Type: cross Abstract: Large Language Models (LLMs) show promise for automated code repair but often struggle with the complex semantic and structural correctness required.

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The Provenance Gap in Clinical AI: Evidence-Traceable Temporal Knowledge Graphs for Rare Disease Reasoning

DGX agent

arXiv:2604.17114v1 Announce Type: new Abstract: Frontier large language models generate clinically accurate outputs, but their citations are often fabricated. We term this the Provenance Gap. We teste

safetyarxiv-cs-cl

21 Apr 2026

TokenChain: A Discrete Speech Chain via Semantic Token Modeling

arXiv:2510.06201v1 Announce Type: cross Abstract: Machine Speech Chain, simulating the human perception-production loop, proves effective in jointly improving ASR and TTS. We propose TokenChain, a ful

applicationsarxiv-cs-lg

Towards Trustworthy Depression Estimation via Disentangled Evidential Learning

arXiv:2604.16579v1 Announce Type: new Abstract: Automated depression estimation is highly vulnerable to signal corruption and ambient noise in real-world deployment. Prevailing deterministic methods p

safetyarxiv-cs-lg

TransXion: A High-Fidelity Graph Benchmark for Realistic Anti-Money Laundering

model-releasesarxiv-cs-lg

arXiv:2604.17420v1 Announce Type: new Abstract: Money laundering poses severe risks to global financial systems, driving the widespread adoption of machine learning for transaction monitoring. However

Uni-MMMU: A Massive Multi-discipline Multimodal Unified Benchmark

model-releasesarxiv-cs-cv

arXiv:2510.13759v3 Announce Type: replace Abstract: Unified multimodal models aim to jointly enable visual understanding and generation, yet current benchmarks rarely examine their true integration. E

UniMesh: Unifying 3D Mesh Understanding and Generation

arXiv:2604.17472v1 Announce Type: new Abstract: Recent advances in 3D vision have led to specialized models for either 3D understanding (e.g., shape classification, segmentation, reconstruction) or 3D

Waking Up Blind: Cold-Start Optimization of Supervision-Free Agentic Trajectories for Grounded Visual Perception

arXiv:2604.17475v1 Announce Type: cross Abstract: Small Vision-Language Models (SVLMs) are efficient task controllers but often suffer from visual brittleness and poor tool orchestration. They typical

safetyarxiv-cs-cl

Weakly-Supervised Referring Video Object Segmentation through Text Supervision

arXiv:2604.17797v1 Announce Type: new Abstract: Referring video object segmentation (RVOS) aims to segment the target instance in a video, referred by a text expression. Conventional approaches are mo

safetyarxiv-cs-cv

Why AI Readiness Is an Organizational Learning Problem, Not a Technology Purchase

arXiv:2604.16369v1 Announce Type: cross Abstract: Global corporate AI investment reached $252.3 billion in 2024, yet only 6% of firms report significant earnings impact. This article argues that AI pr

safetyarxiv-cs-cl

WorldDB: A Vector Graph-of-Worlds Memory Engine with Ontology-Aware Write-Time Reconciliation

arXiv:2604.18478v1 Announce Type: cross Abstract: Persistent memory is the bottleneck separating stateless chatbots from long-running agentic systems. Retrieval-augmented generation (RAG) over flat ve

XEmbodied: A Foundation Model with Enhanced Geometric and Physical Cues for Large-Scale Embodied Environments

arXiv:2604.18484v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models drive next-generation autonomous systems, but training them requires scalable, high-quality annotations from complex

agentsarxiv-cs-cv

ZSG-IAD: A Multimodal Framework for Zero-Shot Grounded Industrial Anomaly Detection

arXiv:2604.17949v1 Announce Type: new Abstract: Deep learning-based industrial anomaly detectors often behave as black boxes, making it hard to justify decisions with physically meaningful defect evid

Advancing Intelligent Sequence Modeling: Evolution, Trade-offs, and Applications of State- Space Architectures from S4 to Mamba

arXiv:2503.18970v3 Announce Type: replace Abstract: Structured State Space Models (SSMs) have emerged as a transformative paradigm in sequence modeling, addressing critical limitations of Recurrent Ne

researcharxiv-cs-lg

Automating Crash Diagram Generation Using Vision-Language Models: A Case Study on Multi-Lane Roundabouts

model-releasesarxiv-cs-ai

arXiv:2604.15332v1 Announce Type: cross Abstract: Crash diagrams are essential tools in transportation safety analysis, yet their manual preparation remains time-consuming and prone to human variabili

Capture the Flags: Family-Based Evaluation of Agentic LLMs via Semantics-Preserving Transformations

arXiv:2602.05523v2 Announce Type: replace-cross Abstract: Agentic large language models (LLMs) are increasingly evaluated on cybersecurity tasks using capture-the-flag (CTF) benchmarks, yet existing p

agentsarxiv-cs-ai

ChemAmp: Amplified Chemistry Tools via Composable Agents

arXiv:2505.21569v3 Announce Type: replace-cross Abstract: Although LLM-based agents are proven to master tool orchestration in scientific fields, particularly chemistry, their single-task performance

agentsarxiv-cs-ai

CoEvolve: Training LLM Agents via Agent-Data Mutual Evolution

arXiv:2604.15840v1 Announce Type: new Abstract: Reinforcement learning for LLM agents is typically conducted on a static data distribution, which fails to adapt to the agent's evolving behavior and le

agentsarxiv-cs-cl

Contact-Aware Planning and Control of Continuum Robots in Highly Constrained Environments

arXiv:2604.15638v1 Announce Type: new Abstract: Continuum robots are well suited for navigating confined and fragile environments, such as vascular or endoluminal anatomy, where contact with surroundi

safetyarxiv-cs-ro

Creating and Evaluating Personas Using Generative AI: A Scoping Review of 81 Articles

arXiv:2504.04927v2 Announce Type: replace-cross Abstract: As generative AI (GenAI) is increasingly applied in persona development to represent real users, understanding the implications and limitation

CRoCoDiL: Continuous and Robust Conditioned Diffusion for Language

arXiv:2603.20210v3 Announce Type: replace-cross Abstract: Masked Diffusion Models (MDMs) provide an efficient non-causal alternative to autoregressive generation but often struggle with token dependen

researcharxiv-cs-ai

Driving Assistance System for Ambulances to Minimise the Vibrations in Patient Cabin

arXiv:2604.16047v1 Announce Type: cross Abstract: The ambulance service is the main transport for diseased or injured people which suffers the same acceleration forces as regular vehicles. These accel

researcharxiv-cs-lg

DyTact: Capturing Dynamic Contacts in Hand-Object Manipulation

arXiv:2506.03103v2 Announce Type: replace Abstract: Reconstructing dynamic hand-object contacts is essential for realistic manipulation in AI character animation, XR, and robotics, yet it remains chal

safetyarxiv-cs-cv

Elon Musk on the rapid advancement of AI and robotics 'I'm confident that if AI and robotics continue to advance which they are advancing ve…

Elon Musk on the rapid advancement of AI and robotics 'I'm confident that if AI and robotics continue to advance which they are advancing very rapidly working will be optional, and people will have an

applicationselon-musk--x

FineSteer: A Unified Framework for Fine-Grained Inference-Time Steering in Large Language Models

arXiv:2604.15488v1 Announce Type: cross Abstract: Large language models (LLMs) often exhibit undesirable behaviors, such as safety violations and hallucinations. Although inference-time steering offer

safetyarxiv-cs-ai

GenHSI: Controllable Generation of Human-Scene Interaction Videos

arXiv:2506.19840v2 Announce Type: replace Abstract: Large-scale pre-trained video diffusion models have exhibited remarkable capabilities in diverse video generation. However, existing solutions face

Tutorials

HiFi-Inpaint: Towards High-Fidelity Reference-Based Inpainting for Generating Detail-Preserving Human-Product Images

arXiv:2603.02210v3 Announce Type: replace Abstract: Human-product images, which showcase the integration of humans and products, play a vital role in advertising, e-commerce, and digital marketing. Th

tutorialsarxiv-cs-cv

Language, Place, and Social Media: Geographic Dialect Alignment in New Zealand

arXiv:2604.15744v1 Announce Type: new Abstract: This thesis investigates geographic dialect alignment in place-informed social media communities, focussing on New Zealand-related Reddit communities. B

safetyarxiv-cs-cl

Mind DeepResearch Technical Report

model-releasesarxiv-cs-ai

arXiv:2604.14518v2 Announce Type: replace Abstract: We present Mind DeepResearch (MindDR), an efficient multi-agent deep research framework that achieves leading performance with only ~30B-parameter m

NEW paper from NVIDIA. EDA tools like ABC have been hand-tuned by humans for decades. New research from NVIDIA shows they can evolve themsel…

NEW paper from NVIDIA. EDA tools like ABC have been hand-tuned by humans for decades. New research from NVIDIA shows they can evolve themselves. The work introduces the first self-evolving logic synth

model-releasesdair-ai--x

Qwen3.5-Omni Technical Report

arXiv:2604.15804v1 Announce Type: new Abstract: In this work, we present Qwen3.5-Omni, the latest advancement in the Qwen-Omni model family. Representing a significant evolution over its predecessor,

'Taking Stock at FAccT': Using Participatory Design to Co-Create a Vision for the Fairness, Accountability and Transparency Community

arXiv:2604.16224v1 Announce Type: cross Abstract: As a relatively new forum, ACM FAccT has become a key space for activists and scholars to critically examine emerging AI and ML technologies. It bring

safetyarxiv-cs-ai

Target-Oriented Pretraining Data Selection via Neuron-Activated Graph

arXiv:2604.15706v1 Announce Type: new Abstract: Everyday tasks come with a target, and pretraining models around this target is what turns them into experts. In this paper, we study target-oriented la

Trajectory Planning for Safe Dual Control with Active Exploration

arXiv:2604.15507v1 Announce Type: new Abstract: Planning safe trajectories under model uncertainty is a fundamental challenge. Robust planning ensures safety by considering worst-case realizations, ye

safetyarxiv-cs-ro

Local Ai

Upload single or multi-view images to ComfyUI’s HY 3D 3.0 nodes for high-fidelity 3D assets—from product displays to game dev, done in minut…

ComfyUI's HY 3D 3.0 nodes enable rapid 3D asset generation from single or multi-view images, producing high-fidelity 3D models suitable for applications including product visualization and game develo

local-aicomfyui--x

VeriGraph: Scene Graphs for Execution Verifiable Robot Planning

arXiv:2411.10446v3 Announce Type: replace-cross Abstract: Recent progress in vision-language models (VLMs) has opened new possibilities for robot task planning, but these models often produce incorrec

agentsarxiv-cs-ai

I am very proud of our team for releasing EDINET-Bench, and it is fantastic to see a Japanese financial dataset recognized at #ICLR2026 this…

I am very proud of our team for releasing EDINET-Bench, and it is fantastic to see a Japanese financial dataset recognized at #ICLR2026 this week. We need more diverse, non-English datasets to evaluat

applicationsdavid-ha--x

19 Apr 2026

Constraints are the catalyst of invention. An infinite search space leads to paralysis. The most creative inventions happen when you are for…

researchfrancois-chollet--x

Constraints are the catalyst of invention. An infinite search space leads to paralysis. The most creative inventions happen when you are forced to solve a problem within appropriately narrow constrain

18 Apr 2026

A Nonlinear Separation Principle: Applications to Neural Networks, Control and Learning

model-releasesarxiv-cs-lg

arXiv:2604.15238v1 Announce Type: cross Abstract: This paper investigates continuous-time and discrete-time firing-rate and Hopfield recurrent neural networks (RNNs), with applications in nonlinear co

CausalDetox: Causal Head Selection and Intervention for Language Model Detoxification

arXiv:2604.14602v1 Announce Type: new Abstract: Large language models (LLMs) frequently generate toxic content, posing significant risks for safe deployment. Current mitigation strategies often degrad

Contract-Coding: Towards Repo-Level Generation via Structured Symbolic Paradigm

model-releasesarxiv-cs-ai

arXiv:2604.13100v1 Announce Type: cross Abstract: The shift toward intent-driven software engineering (often termed 'Vibe Coding') exposes a critical Context-Fidelity Trade-off: vague user intents ove

DVFace: Spatio-Temporal Dual-Prior Diffusion for Video Face Restoration

arXiv:2604.14560v1 Announce Type: new Abstract: Video face restoration aims to enhance degraded face videos into high-quality results with realistic facial details, stable identity, and temporal coher

applicationsarxiv-cs-cv

EviSearch: A Human in the Loop System for Extracting and Auditing Clinical Evidence for Systematic Reviews

arXiv:2604.14165v1 Announce Type: new Abstract: We present EviSearch, a multi-agent extraction system that automates the creation of ontology-aligned clinical evidence tables directly from native tria

Evolving Beyond Snapshots: Harmonizing Structure and Sequence via Entity State Tuning for Temporal Knowledge Graph Forecasting

arXiv:2602.12389v3 Announce Type: replace-cross Abstract: Temporal knowledge graph (TKG) forecasting requires predicting future facts by jointly modeling structural dependencies within each snapshot a

FADPNet: Frequency-Aware Dual-Path Network for Face Super-Resolution

arXiv:2506.14121v2 Announce Type: replace Abstract: Face super-resolution (FSR) under limited computational budgets remains challenging. Existing methods often treat all facial pixels equally, leading

Flow of Truth: Proactive Temporal Forensics for Image-to-Video Generation

arXiv:2604.15003v1 Announce Type: new Abstract: The rapid rise of image-to-video (I2V) generation enables realistic videos to be created from a single image but also brings new forensic demands. Unlik

From Reactive to Proactive: Assessing the Proactivity of Voice Agents via ProVoice-Bench

arXiv:2604.15037v1 Announce Type: cross Abstract: Recent advancements in LLM agents are gradually shifting from reactive, text-based paradigms toward proactive, multimodal interaction. However, existi

Generative Data Augmentation for Skeleton Action Recognition

arXiv:2604.14933v1 Announce Type: new Abstract: Skeleton-based human action recognition is a powerful approach for understanding human behaviour from pose data, but collecting large-scale, diverse, an