Search: “research”

Synthetic Data Generation for Brain-Computer Interfaces: Overview, Benchmarking, and Future Directions

arXiv:2603.12296v2 Announce Type: replace-cross Abstract: Deep learning has achieved transformative performance across diverse domains, largely driven by large-scale and high-quality training data. In

Safety

The Accessibility Capability Boundary: Operational Limits and Expansion Potential of AI-Generated Browser-Native Accessibility Systems

DGX agent

arXiv:2605.19638v1 Announce Type: cross Abstract: As large language models (LLMs) demonstrate increasing competence in synthesizing functional user interfaces, a fundamental question emerges in access

safetyarxiv-cs-ai

20 May 2026

Toward an AI-Powered Computational Testbed for Workforce Policy

arXiv:2605.19064v1 Announce Type: cross Abstract: Workforce transformations are difficult to forecast and costly to mismanage. In particular, the integration of artificial intelligence into knowledge

Trajectory Planning and Control near the Limits: an Open Experimental Benchmark on the RoboRacer Platform

model-releasesarxiv-cs-ro

arXiv:2605.19881v1 Announce Type: new Abstract: We present a modular framework to benchmark new and existing methods for trajectory planning and control in high-acceleration maneuvers that push autono

Agents

When Web Apps Heal Themselves: A MAPE-K Based Approach to Fault Tolerance and Adaptive Recovery

arXiv:2605.19261v1 Announce Type: cross Abstract: Ensuring the reliability and resilience of modern web applications remains a critical challenge due to increasing system complexity and dynamic runtim

agentsarxiv-cs-ai

ZeroSearch: Incentivize the Search Capability of LLMs without Searching

arXiv:2505.04588v3 Announce Type: replace Abstract: Effective information searching is essential for enhancing the reasoning and generation capabilities of large language models (LLMs). Recent researc

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 Feature-Driven Framework for Software Fault Prediction

model-releasesarxiv-cs-lg

arXiv:2605.17611v1 Announce Type: cross Abstract: Software fault prediction (SFP) is a critical task in software engineering, enabling early identification of faults in modules to improve software qua

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

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

Applications

Active Budget Allocation for Efficient Scaling Law Estimation via Surrogate-Guided Pruning

arXiv:2605.17234v1 Announce Type: new Abstract: Predicting model performance at larger scales enables the design of training strategies and architectures tailored to specific performance targets. Empi

applicationsarxiv-cs-lg

Agents

AgentArk: Distilling Multi-Agent Intelligence into a Single LLM Agent

arXiv:2602.03955v2 Announce Type: replace Abstract: While large language model (LLM) multi-agent systems achieve superior reasoning performance through iterative debate, practical deployment is limite

agentsarxiv-cs-ai

AI Agents May Always Fall for Prompt Injections

arXiv:2605.17634v1 Announce Type: cross Abstract: Prompt injection is the most critical vulnerability in deployed AI agents. Despite recent progress, we show that the prevailing defense paradigm (data

safetyarxiv-cs-cl

Alignment Drift in Long-Term Human-LLM Interaction: A Mechanism-Oriented Framework

arXiv:2605.16516v1 Announce Type: cross Abstract: Long-term interaction with LLM-based systems may produce alignment drift: a gradual process in which system outputs become less constrained by the use

ARROW: Augmented Replay for RObust World models

arXiv:2603.11395v2 Announce Type: replace-cross Abstract: Continual reinforcement learning challenges agents to acquire new skills while retaining previously learned ones with the goal of improving pe

Babel: Jailbreaking Safety Attention via Obfuscation Distribution Optimized Sampling

arXiv:2605.17971v1 Announce Type: cross Abstract: Despite rigorous safety alignment, Large Language Models (LLMs) remain vulnerable to jailbreak attacks. Existing black-box methods often rely on heuri

Bench2Drive-Robust: Benchmarking Closed-Loop Autonomous Driving under Deployment Perturbations

model-releasesarxiv-cs-ro

arXiv:2605.18059v1 Announce Type: new Abstract: Robustness is a critical requirement for deploying autonomous driving systems in the real world. Existing robustness benchmarks for autonomous driving h

Beyond Compliance: How AI Could Help Creative Writers by Refusing Them

arXiv:2605.16272v1 Announce Type: cross Abstract: Mainstream creativity support design prioritizes compliant AI for seamless writing interactions, but concerns over inappropriate AI reliance highlight

Breaking Annotation Barriers: Generalized Video Quality Assessment via Ranking-based Self-Supervision

model-releasesarxiv-cs-cv

arXiv:2505.03631v4 Announce Type: replace Abstract: Video quality assessment (VQA) is essential for quantifying perceptual quality in various video processing workflows, spanning from camera capture s

Can LLMs Generate and Solve Linguistic Olympiad Puzzles?

arXiv:2509.21820v2 Announce Type: replace Abstract: In this paper, we introduce a combination of novel and exciting tasks: the solution and generation of linguistic puzzles. We focus on puzzles used i

CAREBench: Evaluating LLMs' Emotion Understanding by Assessing Cognitive Appraisal Reasoning

arXiv:2605.17176v1 Announce Type: new Abstract: Emotion understanding is a core capability for LLMs to interact effectively with humans, yet existing evaluation paradigms rely on discrete emotion labe

CayleyPy RL: Pathfinding and Reinforcement Learning on Cayley Graphs

model-releasesarxiv-cs-lg

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

Continual Learning for VLMs: A Survey and Taxonomy Beyond Forgetting

model-releasesarxiv-cs-cv

arXiv:2508.04227v2 Announce Type: replace Abstract: Vision-language models (VLMs) and the recent surge of Multimodal Large Language Models (MLLMs) have revolutionized artificial intelligence with unpr

CooT: Learning to Coordinate In-Context with Coordination Transformers

arXiv:2506.23549v3 Announce Type: replace Abstract: Effective coordination among unfamiliar partners remains a major challenge in multi-agent systems. Existing approaches, such as population-based met

Deep sequence models tend to memorize geometrically; it is unclear why

arXiv:2510.26745v3 Announce Type: replace-cross Abstract: Deep sequence models are said to store atomic facts predominantly in the form of associative memory: a brute-force lookup of co-occurring enti

EgoIntrospect: An Egocentric Dataset and Benchmark for User-Centric Internal State Reasoning

model-releasesarxiv-cs-cv

arXiv:2605.17262v1 Announce Type: new Abstract: Despite extensive efforts on egocentric video datasets and benchmarks, understanding users' internal states, which is crucial for enabling seamless AI a

Estimating Item Difficulty with Large Language Models as Experts

arXiv:2605.18562v1 Announce Type: cross Abstract: Accurate estimates of item difficulty are essential for valid assessment and effective adaptive learning. However, for newly created tasks, response d

Evaluating Cognitive Age Alignment in Interactive AI Agents

arXiv:2605.17894v1 Announce Type: new Abstract: While agentic AI and its core multimodal large language models (MLLMs) have demonstrated remarkable promise in language and visual reasoning across doma

Evolve the Method, Not the Prompts: Evolutionary Synthesis of Jailbreak Attacks on LLMs

arXiv:2511.12710v2 Announce Type: replace Abstract: Automated red teaming frameworks for Large Language Models (LLMs) have become increasingly sophisticated, yet many still formulate attack optimizati

EvoMemBench: Benchmarking Agent Memory from a Self-Evolving Perspective

arXiv:2605.18421v1 Announce Type: cross Abstract: Recent benchmarks for Large Language Model (LLM) agents mainly evaluate reasoning, planning, and execution. However, memory is also essential for agen

From Demographics to Survey Anchors: Evaluating LLM Agents for Modeling Retirement Attitudes

arXiv:2605.16303v1 Announce Type: cross Abstract: Large language models (LLM) agents may offer tools to predict human responses to surveys. A common technique for defining these agents uses only demog

Agents

Generative AI Advertising as a Problem of Trustworthy Commercial Intervention

arXiv:2605.18673v1 Announce Type: cross Abstract: Major deployed generative AI advertising systems preserve a visible boundary between commercial content and AI-generated responses. Yet empirical rese

agentsarxiv-cs-cl

Generative Artificial Intelligence for Literature Reviews

arXiv:2605.16475v1 Announce Type: cross Abstract: Generative artificial intelligence (GenAI), based on large-language models (LLMs), such as ChatGPT, has taken organizations, academia, and the public

Google just redesigned the search box for the first time in 25 years — here’s why it matters more than you think.

model-releasesventurebeat-ai

For a quarter century, the Google search box has been one of the most recognizable interfaces in computing: a thin white rectangle, a blinking cursor, a few typed words, and a list of blue links. On T

Graph Embedding in the Graph Fractional Fourier Transform Domain

model-releasesarxiv-cs-lg

arXiv:2508.02383v2 Announce Type: replace Abstract: Spectral graph embedding plays a critical role in graph representation learning by generating low-dimensional vector representations from graph spec

GVGAI-LLM: Evaluating Large Language Model Agents with Infinite Games

arXiv:2508.08501v3 Announce Type: replace Abstract: We introduce GVGAI-LLM, a video game benchmark for evaluating the reasoning and problem-solving capabilities of large language models (LLMs). Built

HalluScore: Large Language Model Hallucination Question Answering Benchmark

arXiv:2605.17007v1 Announce Type: new Abstract: Large language models (LLMs) have achieved remarkable progress in natural language generation, but remain susceptible to hallucination. In response to g

High-Resolution Reference Image Assisted Volumetric Super-Resolution of Cardiac Diffusion Weighted Imaging

arXiv:2310.20389v2 Announce Type: replace-cross Abstract: Diffusion Tensor Cardiac Magnetic Resonance (DT-CMR) is the only in vivo method to non-invasively examine the microstructure of the human hear

tutorialsarxiv-cs-cv

HTSC-2025: A Benchmark Dataset of Ambient-Pressure High-Temperature Superconductors for AI-Driven Critical Temperature Prediction

arXiv:2506.03837v2 Announce Type: replace-cross Abstract: The discovery of high-temperature superconducting materials holds great significance for human industry and daily life. In recent years, resea

Industry

I built a tool that shows you what GPT-2 is 'thinking' in real-time as it generates 3D graph of concept activations per token

This post describes a visualization tool that provides real-time insight into GPT-2's internal processing by displaying concept activations as a 3D graph, with each token generation showing which neur

industryr-chatgpt

Introducing OpenAI for Singapore

OpenAI announced its expansion into Singapore, establishing a presence in the Asia-Pacific region to better serve local customers and developers. The announcement likely covers OpenAI's commitment to

model-releasesopenai

Inventorship in AI-Assisted Inventions: Designing an Experiment to Shape Case Law

arXiv:2605.16528v1 Announce Type: cross Abstract: The latest improvements in artificial intelligence (AI) raise new challenges for intellectual property laws, particularly concerning the inventorship

tutorialsarxiv-cs-ai

iPOE: Interpretable Prompt Optimization via Explanations

arXiv:2605.18113v1 Announce Type: new Abstract: Prompt optimization has often been framed as a discrete search problem to find high-performing and robust instructions for an LLM. However, the search r

tutorialsarxiv-cs-cl

KVCapsule: Efficient Sequential KV Cache Compression for Vision-Language Models with Asymmetric Redundancy

arXiv:2605.16439v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have emerged as a critical and fast-growing extension of Large Language Models (LLMs) that enable multimodal reasoning t

Latency-Aware Deep Learning Benchmark for Real-Time Cyber-Physical Attack and Fault Classification in Inverter-Dominated Power Grids

arXiv:2605.17256v1 Announce Type: cross Abstract: This work introduces a latency-aware benchmarking framework for evaluating deep learning models in power system anomaly detection using high-fidelity,

Learning What Evaluators Value: A Reliable Approach to Modeling Evaluator Preferences

arXiv:2605.16615v1 Announce Type: new Abstract: In many applications, human and LLM evaluators use assessments of relevant criteria to create an overall evaluation for an item or individual. For examp

tutorialsarxiv-cs-lg

Linguistic Uncertainty and Reply Engagement on X: A Cross-Domain Replication of the Uncertainty-Reply Asymmetry

arXiv:2605.16289v1 Announce Type: cross Abstract: Linguistic uncertainty is common in social media, but its relationship with engagement remains unclear across languages and topics. Using 2,258 Englis

safetyarxiv-cs-cl

LiTS: A Modular Framework for LLM Tree Search

arXiv:2603.00631v2 Announce Type: replace Abstract: LiTS is a modular Python framework for LLM reasoning via tree search. It decomposes tree search into three reusable components (Policy, Transition,

Applications

Low Latency Gaze Tracking via Latent Optical Sensing

arXiv:2605.17990v1 Announce Type: new Abstract: We present a real-time gaze tracking system that directly acquires task-relevant latent features using a fully passive optical encoder. Instead of formi

applicationsarxiv-cs-cv