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arXiv:2604.11625v1 Announce Type: cross Abstract: Neural operators have emerged as powerful surrogates for partial differential equation (PDE) solvers, yet they are typically trained as monolithic mod

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Model Releases

Scone: Bridging Composition and Distinction in Subject-Driven Image Generation via Unified Understanding-Generation Modeling

DGX agent

arXiv:2512.12675v2 Announce Type: replace-cross Abstract: Subject-driven image generation has advanced from single- to multi-subject composition, while neglecting distinction, the ability to distingui

model-releasesarxiv-cs-ai

14 Apr 2026

Score-matching-based Structure Learning for Temporal Data on Networks

arXiv:2412.07469v3 Announce Type: replace-cross Abstract: Causal discovery is a crucial initial step in establishing causality from empirical data and background knowledge. Numerous algorithms have be

applicationsarxiv-cs-lg

Search-MIND: Training-Free Multi-Modal Medical Image Registration

arXiv:2604.09743v1 Announce Type: cross Abstract: Multi-modal image registration plays a critical role in precision medicine but faces challenges from non-linear intensity relationships and local opti

local-aiarxiv-cs-cv

SEARL: Joint Optimization of Policy and Tool Graph Memory for Self-Evolving Agents

arXiv:2604.07791v2 Announce Type: replace Abstract: Recent advances in Reinforcement Learning with Verifiable Rewards (RLVR) have demonstrated significant potential in single-turn reasoning tasks. Wit

Seeing Through Deception: Uncovering Misleading Creator Intent in Multimodal News with Vision-Language Models

arXiv:2505.15489v4 Announce Type: replace-cross Abstract: The impact of multimodal misinformation arises not only from factual inaccuracies but also from the misleading narratives that creators delibe

Seeing Through Touch: Tactile-Driven Visual Localization of Material Regions

arXiv:2604.11579v1 Announce Type: new Abstract: We address the problem of tactile localization, where the goal is to identify image regions that share the same material properties as a tactile input.

local-aiarxiv-cs-cv

Self-Evolving LLM Memory Extraction Across Heterogeneous Tasks

arXiv:2604.11610v1 Announce Type: new Abstract: As LLM-based assistants become persistent and personalized, they must extract and retain useful information from past conversations as memory. However,

Self-Organizing Dual-Buffer Adaptive Clustering Experience Replay (SODACER) for Safe Reinforcement Learning in Optimal Control

arXiv:2601.06540v2 Announce Type: replace-cross Abstract: This paper proposes a novel reinforcement learning framework, named Self-Organizing Dual-buffer Adaptive Clustering Experience Replay (SODACER

Sheaf Diffusion with Adaptive Local Structure for Spatio-Temporal Forecasting

arXiv:2604.11275v1 Announce Type: new Abstract: Spatio-temporal systems often exhibit highly heterogeneous and non-intuitive responses to localized disruptions, limiting the effectiveness of conventio

local-aiarxiv-cs-lg

SIGMA: An Efficient Heterophilous Graph Neural Network with Fast Global Aggregation

arXiv:2305.09958v5 Announce Type: replace Abstract: Graph neural networks (GNNs) realize great success in graph learning but suffer from performance loss when meeting heterophily, i.e. neighboring nod

researcharxiv-cs-lg

Sign Language Recognition in the Age of LLMs

arXiv:2604.11225v1 Announce Type: cross Abstract: Recent Vision Language Models (VLMs) have demonstrated strong performance across a wide range of multimodal reasoning tasks. This raises the question

Signal-Aware Conditional Diffusion Surrogates for Transonic Wing Pressure Prediction

arXiv:2604.11263v1 Announce Type: cross Abstract: Accurate and efficient surrogate models for aerodynamic surface pressure fields are essential for accelerating aircraft design and analysis, yet deter

researcharxiv-cs-lg

SimBench: Benchmarking the Ability of Large Language Models to Simulate Human Behaviors

arXiv:2510.17516v4 Announce Type: replace-cross Abstract: Large language model (LLM) simulations of human behavior have the potential to revolutionize the social and behavioral sciences, if and only i

Agents

SkVM: Revisiting Language VM for Skills across Heterogenous LLMs and Harnesses

arXiv:2604.03088v3 Announce Type: replace-cross Abstract: LLM agents increasingly adopt skills as a reusable unit of composition. While skills are shared across diverse agent platforms, current system

agentsarxiv-cs-lg

SLALOM: Simulation Lifecycle Analysis via Longitudinal Observation Metrics for Social Simulation

arXiv:2604.11466v1 Announce Type: cross Abstract: Large Language Model (LLM) agents offer a potentially-transformative path forward for generative social science but face a critical crisis of validity

SLM Finetuning for Natural Language to Domain Specific Code Generation in Production

model-releasesarxiv-cs-lg

arXiv:2604.09952v1 Announce Type: new Abstract: Many applications today use large language models for code generation; however, production systems have strict latency requirements that can be difficul

SODA: Semi On-Policy Black-Box Distillation for Large Language Models

arXiv:2604.03873v2 Announce Type: replace-cross Abstract: Black-box knowledge distillation for large language models presents a strict trade-off. Simple off-policy methods (e.g., sequence-level knowle

Sources: at least two US federal agencies and three congressional committees have reached out to Anthropic to test Claude Mythos, quietly bypassing Trump's ban (Politico)

Politico: Sources: at least two US federal agencies and three congressional committees have reached out to Anthropic to test Claude Mythos, quietly bypassing Trump's ban — The Commerce Department's Ce

model-releasestechmeme

Spatio-Temporal Difference Guided Motion Deblurring with the Complementary Vision Sensor

arXiv:2604.10554v1 Announce Type: new Abstract: Motion blur arises when rapid scene changes occur during the exposure period, collapsing rich intra-exposure motion into a single RGB frame. Without exp

applicationsarxiv-cs-cv

SpeechLess: Micro-utterance with Personalized Spatial Memory-aware Assistant in Everyday Augmented Reality

arXiv:2602.00793v2 Announce Type: replace-cross Abstract: Speaking aloud to a wearable AR assistant in public can be socially awkward, and re-articulating the same requests every day creates unnecessa

researcharxiv-cs-cl

STaR-DRO: Stateful Tsallis Reweighting for Group-Robust Structured Prediction

arXiv:2604.09737v1 Announce Type: cross Abstract: Structured prediction requires models to generate ontology-constrained labels, grounded evidence, and valid structure under ambiguity, label skew, and

STARS: Skill-Triggered Audit for Request-Conditioned Invocation Safety in Agent Systems

arXiv:2604.10286v1 Announce Type: new Abstract: Autonomous language-model agents increasingly rely on installable skills and tools to complete user tasks. Static skill auditing can expose capability s

StarVLA-alpha: Reducing Complexity in Vision-Language-Action Systems

arXiv:2604.11757v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have recently emerged as a promising paradigm for building general-purpose robotic agents. However, the VLA landsc

Steered LLM Activations are Non-Surjective

arXiv:2604.09839v1 Announce Type: new Abstract: Activation steering is a popular white-box control technique that modifies model activations to elicit an abstract change in output behavior. It has als

Structural Gating and Effect-aligned Lag-resolved Temporal Causal Discovery Framework with Application to Heat-Pollution Extremes

arXiv:2604.10371v1 Announce Type: new Abstract: This study proposes Structural Gating and Effect-aligned Discovery for Temporal Causal Discovery (SGED-TCD), a novel and general framework for lag-resol

safetyarxiv-cs-lg

STU-PID: Steering Token Usage via PID Controller for Efficient Large Language Model Reasoning

arXiv:2506.18831v2 Announce Type: replace Abstract: Large Language Models employing extended chain-of-thought (CoT) reasoning often suffer from the overthinking phenomenon, generating excessive and re

researcharxiv-cs-cl

Suiren-1.0 Technical Report: A Family of Molecular Foundation Models

arXiv:2603.21942v2 Announce Type: replace-cross Abstract: We introduce Suiren-1.0, a family of molecular foundation models for the accurate modeling of diverse organic systems. Suiren-1.0 comprising t

researcharxiv-cs-ai

Hardware

Sustainable Transformer Neural Network Acceleration with Stochastic Photonic Computing

arXiv:2604.09759v1 Announce Type: cross Abstract: Transformers achieve state-of-the-art performance in natural language processing, vision, and scientific computing, but demand high computation and me

hardwarearxiv-cs-lg

SwinTextUNet: Integrating CLIP-Based Text Guidance into Swin Transformer U-Nets for Medical Image Segmentation

arXiv:2604.10000v1 Announce Type: new Abstract: Precise medical image segmentation is fundamental for enabling computer aided diagnosis and effective treatment planning. Traditional models that rely s

SymphoMotion: Joint Control of Camera Motion and Object Dynamics for Coherent Video Generation

model-releasesarxiv-cs-cv

arXiv:2604.03723v2 Announce Type: replace Abstract: Controlling both camera motion and object dynamics is essential for coherent and expressive video generation, yet current methods typically handle o

Tutorials

TacMan-Turbo: Proactive Tactile Control for Robust and Efficient Articulated Object Manipulation

arXiv:2508.02204v4 Announce Type: replace Abstract: Adept manipulation of articulated objects is essential for robots to operate successfully in human environments. Such manipulation requires both eff

tutorialsarxiv-cs-ro

TAG-Head: Time-Aligned Graph Head for Plug-and-Play Fine-grained Action Recognition

model-releasesarxiv-cs-cv

arXiv:2604.11498v1 Announce Type: new Abstract: Fine-grained human action recognition (FHAR) is challenging because visually similar actions differ by subtle spatio-temporal cues. Many recent systems

TAMISeg: Text-Aligned Multi-scale Medical Image Segmentation with Semantic Encoder Distillation

arXiv:2604.10912v1 Announce Type: new Abstract: Medical image segmentation remains challenging due to limited fine-grained annotations, complex anatomical structures, and image degradation from noise,

TAPNext++: What's Next for Tracking Any Point (TAP)?

arXiv:2604.10582v1 Announce Type: new Abstract: Tracking-Any-Point (TAP) models aim to track any point through a video which is a crucial task in AR/XR and robotics applications. The recently introduc

Task2vec Readiness: Diagnostics for Federated Learning from Pre-Training Embeddings

arXiv:2604.10849v1 Announce Type: cross Abstract: Federated learning (FL) performance is highly sensitive to heterogeneity across clients, yet practitioners lack reliable methods to anticipate how a f

TerraSky3D: Multi-View Reconstructions of European Landmarks in 4K

arXiv:2603.28287v2 Announce Type: replace Abstract: Despite the growing need for data of more and more sophisticated 3D reconstruction pipelines, we can still observe a scarcity of suitable public dat

Hardware

Tessera: Unlocking Heterogeneous GPUs through Kernel-Granularity Disaggregation

arXiv:2604.10180v1 Announce Type: cross Abstract: Disaggregation maps parts of an AI workload to different types of GPUs, offering a path to utilize modern heterogeneous GPU clusters. However, existin

hardwarearxiv-cs-lg

Agents

Text-Guided 6D Object Pose Rearrangement via Closed-Loop VLM Agents

arXiv:2604.09781v1 Announce Type: new Abstract: Vision-Language Models (VLMs) exhibit strong visual reasoning capabilities, yet they still struggle with 3D understanding. In particular, VLMs often fai

agentsarxiv-cs-cv

Text-to-Image Models and Their Representation of People from Different Nationalities Engaging in Activities

model-releasesarxiv-cs-cv

arXiv:2504.06313v5 Announce Type: replace Abstract: This paper investigates how popular text-to-image (T2I) models, DALL-E 3 and Gemini 3 Pro Preview, depict people from 206 nationalities when prompte

The Amazing Agent Race: Strong Tool Users, Weak Navigators

arXiv:2604.10261v1 Announce Type: new Abstract: Existing tool-use benchmarks for LLM agents are overwhelmingly linear: our analysis of six benchmarks shows 55 to 100% of instances are simple chains of

The Augmentation Trap: AI Productivity and the Cost of Cognitive Offloading

arXiv:2604.03501v2 Announce Type: replace-cross Abstract: Experimental evidence confirms that AI tools raise worker productivity, but also that sustained use can erode the expertise on which those gai

The Impact of Federated Learning on Distributed Remote Sensing Archives

arXiv:2604.11562v1 Announce Type: new Abstract: Remote sensing archives are inherently distributed: Earth observation missions such as Sentinel-1, Sentinel-2, and Sentinel-3 have collectively accumula

local-aiarxiv-cs-cv

The Price of Ignorance: Information-Free Quotation for Data Retention in Machine Unlearning

arXiv:2604.11511v1 Announce Type: cross Abstract: When users exercise data deletion rights under the General Data Protection Regulation (GDPR) and similar regulations, mobile network operators face a

safetyarxiv-cs-lg

The Second Challenge on Real-World Face Restoration at NTIRE 2026: Methods and Results

arXiv:2604.10532v1 Announce Type: new Abstract: This paper provides a review of the NTIRE 2026 challenge on real-world face restoration, highlighting the proposed solutions and the resulting outcomes.

applicationsarxiv-cs-cv

THEIA: Learning Complete Kleene Three-Valued Logic in a Pure-Neural Modular Architecture

arXiv:2604.11284v1 Announce Type: cross Abstract: We present THEIA, a modular neural architecture that learns complete Kleene three-valued logic (K3) end-to-end without any external symbolic solver, a

(This is a big part of what was called emergence in earlier academic work on unexpected LLM ability gains)

applicationsethan-mollick--x

Ethan Mollick discusses the concept of 'emergence' in large language models (LLMs), referring to the phenomenon where AI systems appear to suddenly develop unexpected capabilities as they scale. The p

TInR: Exploring Tool-Internalized Reasoning in Large Language Models

arXiv:2604.10788v1 Announce Type: cross Abstract: Tool-Integrated Reasoning (TIR) has emerged as a promising direction by extending Large Language Models' (LLMs) capabilities with external tools durin