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arXiv:2510.20035v3 Announce Type: replace-cross Abstract: Vine copulas offer flexible multivariate dependence modeling and have become widely used in machine learning. Yet, structure learning remains

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Model Releases

TideGS: Scalable Training of Over One Billion 3D Gaussian Splatting Primitives via Out-of-Core Optimization

DGX agent

arXiv:2605.20150v1 Announce Type: new Abstract: Training 3D Gaussian Splatting (3DGS) at billion-primitive scale is fundamentally memory-bound: each Gaussian primitive carries a large attribute vector

model-releasesarxiv-cs-cv

20 May 2026

Time-optimal neural feedback control of nilpotent systems as a binary classification problem

arXiv:2503.17581v2 Announce Type: replace-cross Abstract: A computational method for the synthesis of time-optimal feedback control laws for linear nilpotent systems is proposed. The method is based o

TravExplorer: Cross-Floor Embodied Exploration via Traversability-Aware 3-D Planning

model-releasesarxiv-cs-ro

arXiv:2605.19958v1 Announce Type: new Abstract: Zero-shot Object Navigation (ZSON) has shown promise for open-vocabulary target search in unseen environments, yet most existing systems remain tied to

Tutorials

TwinRL: Digital Twin-Driven Reinforcement Learning for Real-World Robotic Manipulation

arXiv:2602.09023v4 Announce Type: replace Abstract: Despite strong generalization capabilities, Vision-Language-Action (VLA) models remain constrained by the high cost of expert demonstrations and lim

tutorialsarxiv-cs-ro

Understanding and Exploiting Weight Update Sparsity for Communication-Efficient Distributed RL

arXiv:2602.03839v2 Announce Type: replace Abstract: Bandwidth-constrained distributed reinforcement learning (RL) post-training of large language models is bottlenecked by two channels: weight synchro

local-aiarxiv-cs-lg

Universal Skeleton Understanding via Differentiable Rendering and MLLMs

arXiv:2603.18003v4 Announce Type: replace Abstract: Multimodal large language models (MLLMs) exhibit strong visual-language reasoning, yet cannot process structured, non-visual data such as human skel

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What Are LLMs Doing to Scientific Communication? Measuring Changes in Writing Practices and Reading Experience

arXiv:2605.19936v1 Announce Type: new Abstract: Has the style of scientific communication changed due to the growing use of large language models in the writing process? We address this question in th

researcharxiv-cs-cl

4DLidarOpen: An Open 4D FMCW Lidar Dataset for Motion-Aware Autonomous Driving

model-releasesarxiv-cs-ro

arXiv:2605.18074v1 Announce Type: new Abstract: We present 4DLidarOpen, a large-scale open multi-modal dataset for autonomous driving, centered on 4D frequency-modulated continuous-wave (FMCW) Lidar s

A Critical Assessment of PINNs and Operator Learning for Geotechnical Engineering

arXiv:2512.24365v2 Announce Type: replace-cross Abstract: Scientific machine learning (SciML) offers neural-network alternatives to numerical workflows in geotechnical engineering. This paper benchmar

A Pilot Benchmark for NL-to-FOL Translation in Planetary Exploration

model-releasesarxiv-cs-cl

arXiv:2605.17911v1 Announce Type: new Abstract: Future planetary exploration envisions autonomous robotic agents operating under severe communication constraints, without global positioning, and with

A Production-Ready RL Framework for Personalized Utility Tuning with Pareto Sweeping in Pinterest Recommender Systems

arXiv:2605.16344v1 Announce Type: cross Abstract: Large-scale recommenders encode multi-objective trade-offs by combining multiple predicted outcomes into a single utility score. Although this utility

A Readiness-Driven Runtime for Pipeline-Parallel Training under Runtime Variability

arXiv:2605.18750v1 Announce Type: cross Abstract: Pipeline parallelism is a key technique for scaling large-model training, but modern workloads exhibit runtime variability in computation and communic

researcharxiv-cs-lg

A Systematic Analysis of Out-of-Distribution Detection Under Representation and Training Paradigm Shifts

arXiv:2511.11934v3 Announce Type: replace-cross Abstract: We present a systematic benchmark of out-of-distribution (OOD) detection CSFs through a representation-centric lens. Our study spans CNN and V

ACE: Self-Evolving LLM Coding Framework via Adversarial Unit Test Generation and Preference Optimization

arXiv:2605.16299v1 Announce Type: cross Abstract: Large Language Models (LLMs) excel at code generation but remain heavily reliant on large-scale annotated solutions and verification-based supervision

Adaptive Generate-Rank-Verify: Inference-Time Search with Costly Verification

arXiv:2605.17609v1 Announce Type: new Abstract: Many inference-time language-model pipelines combine a cheap reward signal with an expensive verifier, such as exact answer checking in mathematical rea

safetyarxiv-cs-lg

Adversarial Agent Collaboration for Correctness Improvements of C to Safe Rust Translation

arXiv:2510.03879v3 Announce Type: replace-cross Abstract: Translating C to memory-safe languages, like Rust, prevents critical memory safety vulnerabilities that are prevalent in legacy C software. Ev

AgentKernelArena: Generalization-Aware Benchmarking of GPU Kernel Optimization Agents

arXiv:2605.16819v1 Announce Type: cross Abstract: GPU kernel optimization is increasingly critical for efficient deep learning systems, but writing high-performance kernels still requires substantial

AI for Auto-Research: Roadmap & User Guide

arXiv:2605.18661v1 Announce Type: new Abstract: AI-assisted research is crossing a threshold: fully automated systems can now generate research papers for as little as $15, while long-horizon agents c

An Efficient Streaming Video Understanding Framework with Agentic Control

arXiv:2605.17921v1 Announce Type: new Abstract: Streaming video requires handling dynamic information density under strict latency budgets. Yet, existing methods typically employ static strategies, su

safetyarxiv-cs-cv

ArtMesh: Part-Aware Articulated Mesh Fields with Motion-Consistent Dynamics

arXiv:2605.16582v1 Announce Type: new Abstract: We present ArtMesh, a mesh-native method for reconstructing articulated objects explicitly as connected triangle meshes with per-part rigid motion from

AscendOptimizer: Episodic Agent for Ascend NPU Operator Optimization

arXiv:2603.23566v2 Announce Type: replace-cross Abstract: Optimizing AscendC (Ascend C) operators for Ascend NPUs is difficult for two reasons. First, unlike CUDA, the ecosystem offers few public kern

AtlasVA: Self-Evolving Visual Skill Memory for Teacher-Free VLM Agents

arXiv:2605.17933v1 Announce Type: new Abstract: Vision-language model (VLM) agents increasingly rely on memory-augmented reinforcement learning to reuse experience across long-horizon tasks, yet most

researcharxiv-cs-cv

Attention-Guided Fusion of 1D and 2D CNNs for Robust ECG-Based Biometric Recognition

arXiv:2605.17685v1 Announce Type: cross Abstract: Electrocardiogram (ECG)-based biometric recognition has emerged as a promising solution for secure authentication and liveness detection. However, mos

Tutorials

Automated Knowledge Component Generation for Interpretable Knowledge Tracing in Coding Problems

arXiv:2502.18632v4 Announce Type: replace Abstract: Knowledge components (KCs) mapped to problems help model student learning, tracking their mastery levels on fine-grained skills thereby facilitating

tutorialsarxiv-cs-ai

Automated Root-Cause Subclassification and No-Code Fix Generation for Invalid Bug Reports

arXiv:2605.17561v1 Announce Type: cross Abstract: Issues faced when using software are reported in the form of bug reports. However, many bug reports are invalid, meaning they do not require code chan

Beyond Detection: A Structure-Aware Framework for Scene Text Tracking

arXiv:2605.17270v1 Announce Type: new Abstract: Modern visual object trackers show impressive results on general targets, yet their performance drops substantially when dealing with scene text. Althou

Beyond Execution: Static-Analysis Rewards and Hint-Conditioned Diffusion RL for Code Generation

arXiv:2605.17174v1 Announce Type: cross Abstract: Reinforcement Learning (RL) is an important paradigm for aligning Diffusion Language Models (DLMs) toward functional correctness in code generation. H

Beyond Geometry: Efficient Topologically-Grounded Navigation in Complex 3D Environments

model-releasesarxiv-cs-ro

arXiv:2605.17302v1 Announce Type: new Abstract: Ground robot navigation in complex 3D environments is often hindered by geometric ambiguity, where non-traversable structures such as furniture share lo

Beyond Morphology: Quantifying the Diagnostic Power of Color Features in Cancer Classification

arXiv:2605.18522v1 Announce Type: cross Abstract: In histopathology, human experts primarily rely on color as a means of enhancing contrast to interpret tissue morphology, whereas machine vision model

Applications

Beyond Sentiment Classification: A Generative Framework for Emotion Intensity Evaluation in Text

arXiv:2605.16613v1 Announce Type: new Abstract: We introduce a novel approach to emotion modeling that shifts the focus from identification to evaluation, addressing the limitations of discrete classi

applicationsarxiv-cs-cl

Applications

Beyond the Next Port: A Multi-Task Transformer for Forecasting Future Voyage Segment Durations

arXiv:2601.08013v2 Announce Type: replace Abstract: Accurate forecasts of segment-level sailing durations are fundamental to enhancing maritime schedule reliability and optimizing long-term port opera

applicationsarxiv-cs-lg

BLAgent: Agentic RAG for File-Level Bug Localization

arXiv:2605.17965v1 Announce Type: cross Abstract: Bug localization remains a key bottleneck in downstream software maintenance tasks, including root cause analysis, triage, and automated program repai

local-aiarxiv-cs-ai

Breaking the accuracy-resource dilemma: a lightweight adaptive video inference enhancement

arXiv:2601.14568v2 Announce Type: replace-cross Abstract: Existing video inference (VI) enhancement methods typically aim to improve performance by scaling up model sizes and employing sophisticated n

Bridging the Intention-Expression Gap: Aligning Multi-Dimensional Preferences via Hierarchical Relevance Feedback in Text-to-Image Diffusion

arXiv:2603.14936v3 Announce Type: replace Abstract: Users often possess a clear visual intent but struggle to articulate it precisely in language. This intention-expression gap makes aligning generate

safetyarxiv-cs-cv

Agents

Can LLM Agents Be CFOs? Benchmarking Long-Horizon Resource Allocation in an Uncertain Enterprise Environment

arXiv:2603.23638v2 Announce Type: replace Abstract: Large language model (LLM) agents are increasingly tested on complex tasks, but their ability to allocate scarce resources over long horizons remain

agentsarxiv-cs-ai

CANSURF: An ASV-View Can Dataset and Benchmark for Detection and Tracking of Surface-Level Debris

arXiv:2605.16774v1 Announce Type: cross Abstract: Surface-level marine debris remains a practical bottleneck for autonomous clean-up, where small, reflective targets (e.g., aluminum cans) must be dete

Causal Anomaly Detection for Lithium-Ion Battery Degradation

arXiv:2605.17334v1 Announce Type: cross Abstract: Reliable early detection of lithium-ion battery degradation requires health indicators that are physically interpretable and computable from routine c

Causal Attribution via Activation Patching

arXiv:2603.13652v2 Announce Type: replace Abstract: Attribution methods for Vision Transformers (ViTs) aim to identify image regions that influence model predictions, but producing faithful and well-l

local-aiarxiv-cs-cv

Tutorials

CAVE: A Structured Credit Assignment Approach for Fragmented Visual Evidence Reasoning

arXiv:2605.16416v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have achieved strong performance on general multimodal reasoning, yet remain challenged in integrating nonlocal visual i

tutorialsarxiv-cs-ai

CayleyPy RL: Pathfinding and Reinforcement Learning on Cayley Graphs

arXiv:2502.18663v3 Announce Type: replace Abstract: This paper is the second in a series of studies on developing efficient artificial intelligence-based approaches to pathfinding on extremely large g

CHI-Bench: Can AI Agents Automate End-to-End, Long-Horizon, Policy-Rich Healthcare Workflows?

arXiv:2605.16679v1 Announce Type: cross Abstract: End-to-end automation of realistic healthcare operations stresses three capabilities underrepresented in current benchmarks: policy density, decisions

Coarse Semantic Injection for LLM-Conditioned Structured Indoor Prediction

arXiv:2605.16832v1 Announce Type: new Abstract: Large language models (LLMs) have recently been used as structured decoders for indoor understanding from 3D point-token inputs. However, point cloud en

researcharxiv-cs-cv

Code-as-Room: Generating 3D Rooms from Top-Down View Images via Agentic Code Synthesis

arXiv:2605.18451v1 Announce Type: new Abstract: Designing realistic and functional 3D indoor rooms is essential for a wide range of applications, including interior design, virtual reality, gaming, an

CommitDistill: A Lightweight Knowledge-Centric Memory Layer for Software Repositories

arXiv:2605.18284v1 Announce Type: cross Abstract: Software repositories accumulate large amounts of unstructured knowledge in commit messages, pull-request discussions, and issue threads, but develope

CompassAD: Intent-Driven 3D Affordance Grounding in Functionally Competing Objects

arXiv:2604.02060v2 Announce Type: replace Abstract: When told to 'cut the cake,' a robot must choose the knife over nearby scissors, despite both objects affording the same cutting function. In real-w

Constrained Code Generation with Discrete Diffusion

arXiv:2605.16829v1 Announce Type: new Abstract: Discrete diffusion models are a powerful, emerging paradigm for code generation. They construct programs through iterative refinement of partially corru

local-aiarxiv-cs-cl

Content-Style Identification via Differential Independence

arXiv:2605.17827v1 Announce Type: cross Abstract: Generative analysis often models multi-domain observations as nonlinear mixtures of domain-invariant content variables and domain-specific style varia