Search: “papers”

S1-MMAlign: A Large-Scale, Multi-Disciplinary Dataset for Scientific Figure-Text Understanding

arXiv:2601.00264v2 Announce Type: replace Abstract: Multimodal learning has revolutionized general domain tasks, yet its application in scientific discovery is hindered by the profound semantic gap be

safetyarxiv-cs-cv

7 May 2026

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Safety Must Precede the Deployment of Open-Ended AI

DGX agent

arXiv:2502.04512v3 Announce Type: replace Abstract: AI advancements have been significantly driven by a combination of foundation models and curiosity-driven learning aimed at increasing capability an

safetyarxiv-cs-ai

7 May 2026

TNStream: Applying Tightest Neighbors to Micro-Clusters to Define Multi-Density Clusters in Streaming Data

arXiv:2505.00359v2 Announce Type: replace Abstract: In data stream clustering, systematic theory of stream clustering algorithms remains relatively scarce. Recently, density-based methods have gained

7 May 2026

Artificial Jagged Intelligence as Uneven Optimization Energy Allocation Capability Concentration, Redistribution, and Optimization Governance

arXiv:2605.01420v1 Announce Type: new Abstract: Artificial Jagged Intelligence (AJI) denotes a recurring pattern in which large learning systems exhibit strong local capabilities while remaining weak

DeRelayL: Sustainable Decentralized Relay Learning

arXiv:2605.02935v1 Announce Type: new Abstract: In the era of big data, large-scale machine learning models have revolutionized various fields, driving significant advancements. However, large-scale m

Explainable AI for Blind and Low-Vision Users: Navigating Trust, Modality, and Interpretability in the Agentic Era

arXiv:2604.00187v2 Announce Type: replace-cross Abstract: Explainable Artificial Intelligence (XAI) is critical for ensuring trust and accountability, yet its development remains predominantly visual.

Governing What the EU AI Act Excludes: Accountability for Autonomous AI Agents in Smart City Critical Infrastructure

arXiv:2605.01091v1 Announce Type: cross Abstract: When a traffic signal controller adjusts green phases and a grid manager curtails power on the same corridor, each system may comply with its own obli

safetyarxiv-cs-ai

LLM-enabled Social Agents

arXiv:2605.02335v1 Announce Type: cross Abstract: Large Language Models (LLMs) have transformed agent-agent and human-agent interaction by enabling software, physical, and simulation agents to communi

Runtime Evaluation of Procedural Content Generation in an Endless Runner Game Using Autonomous Agents

arXiv:2605.01783v1 Announce Type: new Abstract: Procedural Content Generation (PCG) enables game content to be created algorithmically without direct manual level-design effort, but it introduces a se

The Productivity-Reliability Paradox: Specification-Driven Governance for AI-Augmented Software Development

arXiv:2605.01160v1 Announce Type: cross Abstract: Since 2022, AI-powered coding assistants have produced contradictory evidence: controlled studies report 20-56% productivity gains on well-scoped task

Trustworthy AI Suffers from Invariance Conflicts and Causality is The Solution

arXiv:2605.02640v1 Announce Type: new Abstract: As artificial intelligence (AI), including machine learning (ML) models and foundation models (FMs), is increasingly deployed in high-stakes domains, en

safetyarxiv-cs-ai

A Comprehensive Review of Fish Feeding Behavior Analysis in Aquaculture: Tasks, Techniques, and Applications

arXiv:2502.15311v3 Announce Type: replace Abstract: Fish feeding behavior analysis is a key foundation for intelligent feeding and precision aquaculture management, and plays an important role in impr

applicationsarxiv-cs-cv

Beyond Crash: Hijacking Your Autonomous Vehicle for Fun and Profit

arXiv:2602.07249v2 Announce Type: replace-cross Abstract: Autonomous Vehicles (AVs), especially vision-based AVs, are rapidly being deployed without human operators. As AVs operate in safety-critical

safetyarxiv-cs-lg

Can Causal Discovery Algorithms Help in Generating Legal Arguments?

arXiv:2605.02318v1 Announce Type: cross Abstract: In 2011, Judea Pearl received the Turing Award, considered the Nobel Prize in Computing, for fundamental contributions to artificial intelligence thro

Combining Trained Models in Reinforcement Learning

arXiv:2605.02159v1 Announce Type: new Abstract: Deep reinforcement learning (DRL) has delivered strong results in domains such as Atari and Go, but it still suffers from high sample cost and weak tran

safetyarxiv-cs-lg

Deep learning-based pavement performance modeling using multiple distress indicators and road work history

arXiv:2605.01914v1 Announce Type: new Abstract: The deterioration of pavement is a complex and dynamic process determined by different factors including material, environment, design, and some other u

EditPropBench: Measuring Factual Edit Propagation in Scientific Manuscripts

model-releasesarxiv-cs-cl

arXiv:2605.02083v1 Announce Type: new Abstract: Local factual edits in scientific manuscripts often create non-local revision obligations. If a dataset changes from 215 to 80 documents, claims such as

How Prompts Move Language Model Behavior: Frames, Salience, and Construal as Semantic Control

arXiv:2512.12688v3 Announce Type: replace-cross Abstract: Prompt engineering is widely used to shape large language model behavior, yet it is often treated as a practical heuristic rather than as a fo

researcharxiv-cs-cl

HumanSplatHMR: Closing the Loop Between Human Mesh Recovery and Gaussian Splatting Avatar

arXiv:2605.02784v1 Announce Type: new Abstract: Accurately recovering human pose and appearance from video is an essential component of scene reconstruction, with applications to motion capture, motio

safetyarxiv-cs-cv

Reinforcement Learning for LLM-based Multi-Agent Systems through Orchestration Traces

model-releasesarxiv-cs-cl

arXiv:2605.02801v1 Announce Type: new Abstract: As large language model (LLM) agents evolve from isolated tool users into coordinated teams, reinforcement learning (RL) must optimize not only individu

Rule Extraction in Machine Learning: Chat Incremental Pattern Constructor

arXiv:2208.00335v4 Announce Type: replace Abstract: Rule extraction is a central problem in interpretable machine learning because it seeks to convert opaque predictive behavior into human-readable sy

TIJERE: A Novel Threat Intelligence Joint Extraction Model Based on Analyst Expert Knowledge

arXiv:2605.02041v1 Announce Type: new Abstract: The extraction of entities and relationships from threat intelligence reports into structured formats, such as cybersecurity knowledge graphs, is essent

Unbox Responsible GeoAI: Navigating Climate Extreme and Disaster Mapping

arXiv:2605.00315v1 Announce Type: cross Abstract: As climate extreme and disaster events become more frequent and intense, Geospatial Artificial Intelligence (GeoAI) has emerged as a transformative ap

Can Coding Agents Reproduce Findings in Computational Materials Science?

model-releasesarxiv-cs-cl

arXiv:2605.00803v1 Announce Type: cross Abstract: Large language models are increasingly deployed as autonomous coding agents and have achieved remarkably strong performance on software engineering be

4 May 2026

Tutorials

Efficient Mutation Testing of Quantum Machine Learning Models

arXiv:2605.00107v1 Announce Type: cross Abstract: Quantum machine learning integrates the strengths of quantum computing and machine learning, enabling models to learn complex features using fewer par

tutorialsarxiv-cs-lg

4 May 2026

AI Inference as Relocatable Electricity Demand: A Latency-Constrained Energy-Geography Framework

arXiv:2604.27855v1 Announce Type: cross Abstract: AI inference is becoming a persistent and geographically distributed source of electricity demand. Unlike many traditional electrical loads, inference

applicationsarxiv-cs-ai

Evaluating Epistemic Guardrails in AI Reading Assistants: A Behavioral Audit of a Minimal Prototype

arXiv:2604.27275v1 Announce Type: cross Abstract: Large language model (LLM) reading assistants are increasingly used in settings that require interpretation rather than simple retrieval. In these con

Mixed Precision Training of Neural ODEs

arXiv:2510.23498v2 Announce Type: replace-cross Abstract: Exploiting low-precision computations has become a standard strategy in deep learning to address the growing computational costs imposed by ev

Remaining Useful Life Estimation for Turbofan Engines: A Comparative Study of Classical, CNN, and LSTM Approaches

arXiv:2604.27234v1 Announce Type: new Abstract: Remaining Useful Life (RUL) estimation is a critical component of Prognostics and Health Management (PHM), enabling proactive maintenance scheduling and

Semantic Variational Bayes Based on Semantic Information G Theory for Solving Latent Variables

arXiv:2408.13122v2 Announce Type: replace-cross Abstract: The Variational Bayesian method (VB) is used to solve the probability distributions of latent variables with the minimum free energy criterion

Simple Self-Conditioning Adaptation for Masked Diffusion Models

arXiv:2604.26985v1 Announce Type: cross Abstract: Masked diffusion models (MDMs) generate discrete sequences by iterative denoising under an absorbing masking process. In standard masked diffusion, if

Theory Under Construction: Orchestrating Language Models for Research Software Where the Specification Evolves

arXiv:2604.27209v1 Announce Type: cross Abstract: Large language models can now generate substantial code and draft research text, but research-software projects require more than either artifact alon

Data Balancing Strategies: A Systematic Survey of Resampling and Augmentation Methods

arXiv:2505.13518v2 Announce Type: replace-cross Abstract: Imbalanced datasets, where one class significantly outnumbers others, remain a persistent challenge in machine learning, often biasing predict

30 Apr 2026

LATTICE: Evaluating Decision Support Utility of Crypto Agents

arXiv:2604.26235v1 Announce Type: cross Abstract: We introduce LATTICE, a benchmark for evaluating the decision support utility of crypto agents in realistic user-facing scenarios. Prior crypto agent

30 Apr 2026

BEVal: A Cross-dataset Evaluation Study of BEV Segmentation Models for Autonomous Driving

arXiv:2408.16322v4 Announce Type: replace Abstract: Current research in semantic bird's-eye view segmentation for autonomous driving focuses solely on optimizing neural network models using a single d

agentsarxiv-cs-cv

29 Apr 2026

Is the Modality Gap a Bug or a Feature? A Robustness Perspective

arXiv:2603.29080v2 Announce Type: replace Abstract: Many modern multi-modal models (e.g. CLIP) seek an embedding space in which the two modalities are aligned. Somewhat surprisingly, almost all existi

applicationsarxiv-cs-cv

29 Apr 2026

Agentic Witnessing: Pragmatic and Scalable TEE-Enabled Privacy-Preserving Auditing

arXiv:2604.24203v1 Announce Type: cross Abstract: Auditing the semantic properties of proprietary data creates a fundamental tension: verification requires transparent access, while proprietary rights

On the Convergence Theory of Pipeline Gradient-based Analog In-memory Training

arXiv:2410.15155v3 Announce Type: replace Abstract: Aiming to accelerate the training of large deep neural networks (DNN) in an energy-efficient way, analog in-memory computing (AIMC) emerges as a sol

Tutorials

PEPS: Positional Encoding Projected Sampling -- Extended

arXiv:2604.24167v1 Announce Type: new Abstract: Implicit neural representations (INRs) are increasingly being used as tools to map coordinates to signals, encompassing applications from neural fields

tutorialsarxiv-cs-cv

Revisable by Design: A Theory of Streaming LLM Agent Execution

arXiv:2604.23283v1 Announce Type: new Abstract: Current LLM agents operate under an implicit but universal assumption: execution is a transaction -- the user submits a request, the agent works in isol

agentsarxiv-cs-lg

Seeing Is No Longer Believing: Frontier Image Generation Models, Synthetic Visual Evidence, and Real-World Risk

arXiv:2604.24197v1 Announce Type: cross Abstract: Frontier image generation has moved from artistic synthesis toward synthetic visual evidence. Systems such as GPT Image 2, Nano Banana Pro, Nano Banan

Towards Automated Ontology Generation from Unstructured Text: A Multi-Agent LLM Approach

arXiv:2604.23090v1 Announce Type: new Abstract: Automatically generating formal ontologies from unstructured natural language remains a central challenge in knowledge engineering. While large language

Associativity-Peakiness Metric for Contingency Tables

arXiv:2604.22655v1 Announce Type: new Abstract: For the use case of comparing the performance of clustering algorithms whose output is a contingency table, a single performance metric for contingency

BLAST: Benchmarking LLMs with ASP-based Structured Testing

arXiv:2604.22306v1 Announce Type: cross Abstract: Large Language Models (LLMs) have demonstrated remarkable performance across a broad spectrum of tasks, including natural language understanding, dial

dWorldEval: Scalable Robotic Policy Evaluation via Discrete Diffusion World Model

arXiv:2604.22152v1 Announce Type: new Abstract: Evaluating robotics policies across thousands of environments and thousands of tasks is infeasible with existing approaches. This motivates the need for

safetyarxiv-cs-ro

Generating Synthetic Malware Samples Using Generative AI

arXiv:2604.22084v1 Announce Type: new Abstract: Malware attacks have a significant negative impact on organizations of varied scales in the field of cybersecurity. Recently, malware researchers have i

QDTraj: Exploration of Diverse Trajectory Primitives for Articulated Objects Robotic Manipulation

arXiv:2604.22551v1 Announce Type: cross Abstract: Thanks to the latest advances in learning and robotics, domestic robots are beginning to enter homes, aiming to execute household chores autonomously.

Sound Agentic Science Requires Adversarial Experiments

arXiv:2604.22080v1 Announce Type: new Abstract: LLM-based agents are rapidly being adopted for scientific data analysis, automating tasks once limited by human time and expertise. This capability is o