All entries

TimesNet-Gen: Deep Learning-based Site Specific Strong Motion Generation

arXiv:2512.04694v3 Announce Type: replace Abstract: Effective earthquake risk reduction relies on accurate site-specific evaluations, which require models capable of representing the influence of loca

local-aiarxiv-cs-lg

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Timing is Everything: Temporal Scaffolding of Semantic Surprise in Humor

DGX agent

arXiv:2605.00143v1 Announce Type: new Abstract: Humor is a fundamental cognitive phenomenon in which humans derive pleasure from the expectation violations and their resolution, exemplifying the brain

researcharxiv-cs-cl

4 May 2026

Token Arena: A Continuous Benchmark Unifying Energy and Cognition in AI Inference

arXiv:2605.00300v1 Announce Type: cross Abstract: Public inference benchmarks compare AI systems at the model and provider level, but the unit at which deployment decisions are actually made is the en

Token Sparse Attention: Efficient Long-Context Inference with Interleaved Token Selection

arXiv:2602.03216v2 Announce Type: replace Abstract: The quadratic complexity of attention remains the central bottleneck in long-context inference for large language models. Prior acceleration methods

researcharxiv-cs-cl

TokenWeave: Efficient Compute-Communication Overlap for Distributed LLM Inference

arXiv:2505.11329v5 Announce Type: replace-cross Abstract: Distributed inference of large language models (LLMs) using tensor parallelism can introduce communication overheads of 20% even over GPUs con

local-aiarxiv-cs-lg

Agents

ToolGrad: Efficient Tool-use Dataset Generation with Textual 'Gradients'

arXiv:2508.04086v2 Announce Type: replace Abstract: Prior work synthesizes tool-use LLM datasets by first generating a user query, followed by complex tool-use annotations like depth-first search (DFS

agentsarxiv-cs-cl

Towards A Generative Protein Evolution Machine with DPLM-Evo

arXiv:2605.00182v1 Announce Type: new Abstract: Proteins are shaped by gradual evolution under biophysical and functional constraints. Protein language models learn rich evolutionary constraints from

safetyarxiv-cs-lg

Towards Robust and Scalable Density-based Clustering via Graph Propagation

arXiv:2605.00390v1 Announce Type: new Abstract: We present extit{CluProp}, a novel framework that reimagines varied-density clustering in high-dimensional spaces as a label propagation process over ne

Trading off rewards and errors in multi-armed bandits

arXiv:2605.00488v1 Announce Type: new Abstract: In multi-armed bandits, the most-explored arms are the most informative, while reward maximization typically pulls only the best arm. We study the trade

Trees to Flows and Back: Unifying Decision Trees and Diffusion Models

arXiv:2605.00414v1 Announce Type: new Abstract: Decision trees and diffusion models are ostensibly disparate model classes, one discrete and hierarchical, the other continuous and dynamic. This work u

Trident: Improving Malware Detection with LLMs and Behavioral Features

arXiv:2605.00297v1 Announce Type: cross Abstract: Traditionally, machine learning methods for PE malware detection have relied on static features like byte histograms, string information, and PE heade

TURBOTEST: Learning When Less is Enough through Early Termination of Internet Speed Tests

arXiv:2510.21141v2 Announce Type: replace-cross Abstract: Internet speed tests are indispensable for users, ISPs, and policymakers, but their static flooding-based design imposes growing costs: a sing

Two-View Accumulation as the Primary Training Lever for Hybrid-Capture Gaussian Splatting: A Variance-Decomposition View of When Gradient Surgery Helps

arXiv:2605.00052v1 Announce Type: new Abstract: Hybrid-capture novel view synthesis combines images at substantially different camera distances (e.g., aerial drone and ground-level views). Standard 3D

Uncertainty Modeling for Multi-Objective RTA Interception with Distillation Acceleration

arXiv:2511.05582v2 Announce Type: replace Abstract: Real-Time Auction (RTA) Interception aims to filter out invalid or irrelevant traffic to enhance the integrity and reliability of downstream data. H

Understanding Cognitive States from Head & Hand Motion Data

arXiv:2509.24255v2 Announce Type: replace-cross Abstract: As virtual reality (VR) becomes widespread, head and hand motion data captured by consumer systems has become substantially more common. Howev

Uniform-Correct Policy Optimization: Breaking RLVR's Indifference to Diversity

arXiv:2605.00365v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has achieved substantial gains in single-attempt accuracy (Pass@1) on reasoning tasks, yet often

UniVidX: A Unified Multimodal Framework for Versatile Video Generation via Diffusion Priors

arXiv:2605.00658v1 Announce Type: new Abstract: Recent progress has shown that video diffusion models (VDMs) can be repurposed for diverse multimodal graphics tasks. However, existing methods often tr

Unlearning Offline Stochastic Multi-Armed Bandits

arXiv:2605.00638v1 Announce Type: new Abstract: Machine unlearning aims to unlearn data points from a learned model, offering a principled way to process data-deletion requests and mitigate privacy ri

Unlearning What Matters: Token-Level Attribution for Precise Language Model Unlearning

arXiv:2605.00364v1 Announce Type: new Abstract: Machine unlearning has emerged as a critical capability for addressing privacy, safety, and regulatory concerns in large language models (LLMs). Existin

Unlocking Zero-Shot Geospatial Reasoning via Indirect Rewards

arXiv:2510.00072v2 Announce Type: replace Abstract: Training robust reasoning vision-language models (VLMs) in rare domains (such as geospatial) is fundamentally constrained by supervision scarcity. W

Unpaired Image Deraining Using Reward-Guided Self-Reinforcement Strategy

arXiv:2605.00719v1 Announce Type: new Abstract: Unsupervised deraining has attracted attention for its ability to learn the real-world distribution of rain without paired supervision. However, the lac

Unsupervised Denoising of Real Clinical Low Dose Liver CT with Perceptual Attention Networks

arXiv:2605.00793v1 Announce Type: cross Abstract: With the development of deep learning, medical image processing has been widely used to assist clinical research. This paper focuses on the denoising

Value Explicit Pretraining for Learning Transferable Representations

arXiv:2312.12339v3 Announce Type: replace Abstract: Understanding visual inputs for a given task amidst varied changes is a key challenge posed by visual reinforcement learning agents. We propose exti

VecSet-Edit: Unleashing Pre-trained LRM for Mesh Editing from Single Image

arXiv:2602.04349v2 Announce Type: replace Abstract: 3D editing has emerged as a critical research area to provide users with flexible control over 3D assets. While current editing approaches predomina

Vesselpose: Vessel Graph Reconstruction from Learned Voxel-wise Direction Vectors in 3D Vascular Images

model-releasesarxiv-cs-cv

arXiv:2605.00538v1 Announce Type: new Abstract: Blood vessel segmentation and -tracing are essential tasks in many medical imaging applications. Although numerous methods exist, the prevailing segment

VGR: Visual Grounded Reasoning

arXiv:2506.11991v3 Announce Type: replace-cross Abstract: In the field of multimodal chain-of-thought (CoT) reasoning, existing approaches predominantly rely on reasoning on pure language space, which

VideoDetective: Clue Hunting via both Extrinsic Query and Intrinsic Relevance for Long Video Understanding

arXiv:2603.22285v2 Announce Type: replace Abstract: Long video understanding remains challenging for multimodal large language models (MLLMs) due to limited context windows, which necessitate identify

ViLegalNLI: Natural Language Inference for Vietnamese Legal Texts

arXiv:2605.00116v1 Announce Type: new Abstract: In this article, we introduce ViLegalNLI, the first large-scale Vietnamese Natural Language Inference (NLI) dataset specifically constructed for the leg

VkSplat: High-Performance 3DGS Training in Vulkan Compute

arXiv:2605.00219v1 Announce Type: new Abstract: We present VkSplat, a high-performance, cross-vendor 3D Gaussian Splatting (3DGS) training pipeline implemented fully in Vulkan compute, addressing perf

local-aiarxiv-cs-cv

VLAs are Confined yet Capable of Generalizing to Novel Instructions

model-releasesarxiv-cs-ro

arXiv:2505.03500v5 Announce Type: replace Abstract: Vision-language-action models (VLAs) often achieve high performance on demonstrated tasks but struggle significantly when required to extrapolate, c

VLBiMan: Vision-Language Anchored One-Shot Demonstration Enables Generalizable Bimanual Robotic Manipulation

arXiv:2509.21723v4 Announce Type: replace Abstract: Achieving generalizable bimanual manipulation requires systems that can learn efficiently from minimal human input while adapting to real-world unce

safetyarxiv-cs-ro

VQ-SAD: Vector Quantized Structure Aware Diffusion For Molecule Generation

arXiv:2605.00354v1 Announce Type: new Abstract: Many diffusion based molecule generation methods ignore the symbolic information of molecules and represent the atom and bond type as one hot representa

Wasserstein Distributionally Robust Regret Optimization for Reinforcement Learning from Human Feedback

arXiv:2605.00155v1 Announce Type: cross Abstract: Reinforcement learning from human feedback (RLHF) has become a core post-training step for aligning large language models, yet the reward signal used

Applications

Weisfeiler Lehman Test on Combinatorial Complexes: Generalized Expressive Power of Topological Neural Networks

arXiv:2605.00725v1 Announce Type: new Abstract: Combinatorial complexes have unified set-based (e.g., graphs, hypergraphs) and part-whole (e.g., simplicial, cellular complexes) structures into a commo

applicationsarxiv-cs-lg

'What Are You Really Trying to Do?': Co-Creating Life Goals from Everyday Computer Use

arXiv:2605.00497v1 Announce Type: cross Abstract: Recent advances in user modeling make it feasible to conduct open-ended inference over a person's everyday computer use. Despite longstanding visions

researcharxiv-cs-cl

Tutorials

What Don't You Understand? Using Large Language Models to Identify and Characterize Student Misconceptions About Challenging Topics

arXiv:2605.00294v1 Announce Type: new Abstract: This study presents a systematic approach to identifying and characterizing student misconceptions in online learning environments through a novel combi

tutorialsarxiv-cs-cl

What Physics do Data-Driven MoCap-to-Radar Models Learn?

arXiv:2605.00018v1 Announce Type: new Abstract: Data-driven MoCap-to-radar models generate plausible micro-Doppler spectrograms, but do they actually learn the underlying physics? We introduce a physi

safetyarxiv-cs-lg

Tutorials

When Do Diffusion Models learn to Generate Multiple Objects?

arXiv:2605.00273v1 Announce Type: new Abstract: Text-to-image diffusion models achieve impressive visual fidelity, yet they remain unreliable in multi-object generation. Despite extensive empirical ev

tutorialsarxiv-cs-cv

When LLMs Stop Following Steps: A Diagnostic Study of Procedural Execution in Language Models

arXiv:2605.00817v1 Announce Type: new Abstract: Large language models (LLMs) often achieve strong performance on reasoning benchmarks, but final-answer accuracy alone does not show whether they faithf

When RAG Chatbots Expose Their Backend: An Anonymized Case Study of Privacy and Security Risks in Patient-Facing Medical AI

arXiv:2605.00796v1 Announce Type: cross Abstract: Background: Patient-facing medical chatbots based on retrieval-augmented generation (RAG) are increasingly promoted to deliver accessible, grounded he

When Structure Doesn't Help: LLMs Do Not Read Text-Attributed Graphs as Effectively as We Expected

arXiv:2511.16767v2 Announce Type: replace Abstract: Graphs provide a unified representation of semantic content and relational structure, making them a natural fit for domains such as molecular modeli

Why Do LLMs Struggle in Strategic Play? Broken Links Between Observations, Beliefs, and Actions

arXiv:2605.00226v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly tasked with strategic decision-making under incomplete information, such as in negotiation and policymakin

WildfireVLM: AI-powered Analysis for Early Wildfire Detection and Risk Assessment Using Satellite Imagery

arXiv:2602.13305v2 Announce Type: replace Abstract: Wildfires are a growing threat to ecosystems, human lives, and infrastructure, with their frequency and intensity rising due to climate change and h

World Model for Robot Learning: A Comprehensive Survey

arXiv:2605.00080v1 Announce Type: cross Abstract: World models, which are predictive representations of how environments evolve under actions, have become a central component of robot learning. They s

Applications

3D Reconstruction Techniques in the Manufacturing Domain: Applications, Research Opportunities and Use Cases

arXiv:2604.28064v1 Announce Type: new Abstract: This comprehensive review examines the evolution and the current state of the art in three-dimensional (3D) reconstruction techniques in manufacturing a

applicationsarxiv-cs-cv

3D-ReGen: A Unified 3D Geometry Regeneration Framework

arXiv:2604.28134v1 Announce Type: new Abstract: We consider the problem of regenerating 3D objects from 2D images and initial 3D shapes. Most 3D generators operate in a one-shot fashion, converting te

A Collective Variational Principle Unifying Bayesian Inference, Game Theory, and Thermodynamics

arXiv:2604.27942v1 Announce Type: new Abstract: Collective intelligence emerges across biological, physical, and artificial systems without central coordination, yet a unifying principle governing suc

local-aiarxiv-cs-ai

A decision-theoretic approach to dealing with uncertainty in quantum mechanics

arXiv:2503.20607v3 Announce Type: replace-cross Abstract: We provide a decision-theoretic framework for dealing with uncertainty in quantum mechanics. This uncertainty is two-fold: on the one hand the

researcharxiv-cs-ai