Search: “tools”

FusionCell: Cross-Attentive Fusion of Layout Geometry and Netlist Topology for Standard-Cell Performance Prediction

arXiv:2605.20287v1 Announce Type: cross Abstract: Standard cells form the building blocks of digital circuits, so their delay and power critically influence chip-level performance; yet characterizatio

researcharxiv-cs-cv

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Large Language Models Unpack Complex Political Opinions through Target-Stance Extraction

DGX agent

arXiv:2603.23531v2 Announce Type: replace Abstract: Political polarization emerges from a complex interplay of beliefs about policies, figures, and issues. However, most computational analyses reduce

researcharxiv-cs-cl

21 May 2026

Learning First Integrals via Backward-Generated Data and Guided Reinforcement Learning

arXiv:2605.21160v1 Announce Type: new Abstract: The discovery of first integrals is of fundamental scientific importance for understanding conservation laws in dynamical systems. However, existing sym

Learning-to-Defer with Expert-Conditional Advice

model-releasesarxiv-cs-lg

arXiv:2603.14324v3 Announce Type: replace-cross Abstract: Learning-to-Defer routes each input to the expert that minimizes expected cost, but it assumes that the information available to every expert

LLMs on the Line: Data Determines Loss-to-Loss Scaling Laws

arXiv:2502.12120v3 Announce Type: replace-cross Abstract: Scaling laws guide the development of large language models (LLMs) by offering estimates for the optimal balance of model size, tokens, and co

Mahjax: A GPU-Accelerated Mahjong Simulator for Reinforcement Learning in JAX

arXiv:2605.20577v1 Announce Type: cross Abstract: Riichi Mahjong is a multi-player, imperfect-information game characterized by stochasticity and high-dimensional state spaces. These attributes presen

safetyarxiv-cs-lg

Mem-pi: Adaptive Memory through Learning When and What to Generate

arXiv:2605.21463v1 Announce Type: new Abstract: We present Mem-pi, a framework for adaptive memory in large language model (LLM) agents, where useful guidance is generated on demand rather than retrie

agentsarxiv-cs-cl

PACD-Net: Pseudo-Augmented Contrastive Distillation for Glycemic Control Estimation from SMBG

arXiv:2605.20751v1 Announce Type: new Abstract: Effective diabetes management requires continuous monitoring of glycemic levels. Clinically, glycemic control is assessed using metrics such as Time in

tutorialsarxiv-cs-lg

Hardware

PlexRL: Cluster-Level Orchestration of Serviceized LLM Execution for RLVR

arXiv:2605.20863v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has recently unlocked strong reasoning capabilities in large language models (LLMs), triggering

hardwarearxiv-cs-lg

Post-Hoc Understanding of Metaphor Processing in Decoder-Only Language Models via Conditional Scale Entropy

arXiv:2605.21391v1 Announce Type: new Abstract: Metaphor requires a language model to resolve a token whose contextual meaning diverges from its basic literal sense. Understanding how transformer mode

Praxium: Diagnosing Cloud Anomalies with AI-based Telemetry and Dependency Analysis

arXiv:2603.23890v2 Announce Type: replace-cross Abstract: As the modern microservice architecture for cloud applications grows in popularity, cloud services are becoming increasingly complex and more

Puzzled By ChatGPT? No more! A Jigsaw Puzzle to Promote AI Literacy and Awareness

arXiv:2605.20404v1 Announce Type: new Abstract: The rapid adoption of Generative AI, including LLM-based chatbots like ChatGPT, has highlighted the need for accessible ways to support public understan

tutorialsarxiv-cs-cl

Reviving Error Correction in Modern Deep Time-Series Forecasting

arXiv:2605.21088v1 Announce Type: new Abstract: Modern deep-learning models have achieved remarkable success in time-series forecasting. Yet, their performance degrades in long-term prediction due to

Local Ai

The General Theory of Localization Methods

arXiv:2605.20635v1 Announce Type: new Abstract: This paper proposes a general machine learning framework called the localization method, which is fundamentally built on two core concepts: localization

local-aiarxiv-cs-lg

Understanding Model Behavior in Monocular Polyp Sizing

arXiv:2605.20461v1 Announce Type: new Abstract: Accurate polyp size stratification guides surveillance decisions, with lesions larger than 5 mm typically requiring closer follow-up. However, monocular

researcharxiv-cs-cv

A Case for Agentic Tuning: From Documentation to Action in PostgreSQL

arXiv:2605.19988v1 Announce Type: cross Abstract: Documentation has long guided computer system tuning by distilling expert knowledge into per-parameter recommendations. Yet such guides capture only w

A Multi-Dimensional Clustering Approach for Identifying Inborn Errors of Immunity

arXiv:2605.18880v1 Announce Type: cross Abstract: Rare diseases such as inborn errors of immunity (IEI) require early diagnosis to prevent end organ damage and improve quality of life. Hurdles in acce

tutorialsarxiv-cs-cv

A novel YOLO26-MoE optimized by an LLM agent for insulator fault detection considering UAV images

arXiv:2605.19595v1 Announce Type: cross Abstract: The inspection of electrical power line insulators is essential for ensuring grid reliability and preventing failures caused by damaged or degraded in

agentsarxiv-cs-ai

Accurate, Efficient, and Explainable Deep Learning Approaches for Environmental Science Problems

arXiv:2605.19366v1 Announce Type: new Abstract: Environmental science plays a pivotal role in safeguarding ecosystems, a domain driven by large-scale, heterogeneous data. In the big data era, artifici

Bayesian Symbolic Regression for Missing Physics

arXiv:2603.14918v2 Announce Type: replace-cross Abstract: Model-based approaches for (bio)process systems often suffer from incomplete knowledge of the underlying physical, chemical, or biological law

tutorialsarxiv-cs-lg

ClinSeekAgent: Automating Multimodal Evidence Seeking for Agentic Clinical Reasoning

arXiv:2605.20176v1 Announce Type: new Abstract: Large language models (LLMs) and agentic systems have shown promise for clinical decision support, but existing works largely assume that evidence has a

Local Ai

Code-Guided Reasoning for Small Language Models: Evaluating Executable MCQA Scaffolds

arXiv:2605.18827v1 Announce Type: cross Abstract: Multiple-choice QA benchmarks usually evaluate small language models (SLMs) as direct answerers, but deployed language-model systems increasingly rely

local-aiarxiv-cs-lg

DecisionBench: A Benchmark for Emergent Delegation in Long-Horizon Agentic Workflows

arXiv:2605.19099v1 Announce Type: new Abstract: We introduce DecisionBench, a benchmark substrate for emergent delegation in long-horizon agentic workflows. The substrate fixes a task suite (GAIA, tau

Distributional AGI Safety

arXiv:2512.16856v2 Announce Type: replace Abstract: AI safety and alignment research has predominantly been focused on methods for safeguarding individual AI systems, resting on the assumption of an e

safetyarxiv-cs-ai

DLEBench: Evaluating Small-scale Object Editing Ability for Instruction-based Image Editing Model

arXiv:2602.23622v2 Announce Type: replace-cross Abstract: Significant progress has been made in the field of Instruction-based Image Editing Models (IIEMs). However, while these models demonstrate pla

Enabling Real-Time Colonoscopic Polyp Segmentation on Commodity CPUs via Ultra-Lightweight Architecture

arXiv:2602.04381v2 Announce Type: replace-cross Abstract: Real-time polyp segmentation is essential for early colorectal cancer detection, yet clinical deployment remains blocked by GPU dependency. We

EngiAI: A Multi-Agent Framework and Benchmark Suite for LLM-Driven Engineering Design

arXiv:2605.19743v1 Announce Type: new Abstract: Large Language Model (LLM) agents are increasingly applied to engineering design tasks, yet existing evaluation frameworks do not adequately address mul

ESLD (External Surrogate Latent Defense): A Latent-Space Architecture for Faster, Stronger Prompt-Injection Defense

arXiv:2605.18918v1 Announce Type: cross Abstract: Modern AI assistants are agentic. To answer a single user request, the underlying language model pulls in information from many sources, such as web s

safetyarxiv-cs-ai

Evaluating Memory Condensation Strategies for Coding Agents in Data-Driven Scientific Discovery

arXiv:2605.18854v1 Announce Type: new Abstract: Coding agents accumulate extensive context during long-running tasks, yet fixed context windows force practitioners to choose between truncation and tas

tutorialsarxiv-cs-lg

Fine-Tuning Without Forgetting via Loss-Adaptive Learning Rates

arXiv:2605.20005v1 Announce Type: new Abstract: Fine-tuning large language models on new data improves task performance but degrades capabilities learned during pretraining, a phenomenon known as cata

GeoX: Mastering Geospatial Reasoning Through Self-Play and Verifiable Rewards

arXiv:2605.20006v1 Announce Type: new Abstract: Geospatial reasoning requires solving image-grounded problems over the complex spatial structure of a scene. However, developing this capability is hind

Graph Neural Networks for Community Detection in Graph Signal Analysis

model-releasesarxiv-cs-lg

arXiv:2605.19733v1 Announce Type: cross Abstract: Community detection is a central problem in graph analysis, with applications ranging from network science to graph signal processing. In recent years

Guiding Neuro-Symbolic Scenario Generation with Spatio-Temporal Logic

arXiv:2605.19038v1 Announce Type: cross Abstract: The rapid advancement of autonomous driving (AD) technologies has outpaced the development of robust safety evaluation methods. Conventional testing r

safetyarxiv-cs-lg

Lying Is Just a Phase: The Hidden Alignment Transition in Language Model Scaling

arXiv:2605.18838v1 Announce Type: cross Abstract: Scaling laws predict loss from compute but not how capabilities interact. We measure the coupling between reasoning and truthfulness across 63 base mo

Mathematical Reasoning in Large Language Models: Benchmarks, Architectures, Evaluation, and Open Challenges

arXiv:2605.19723v1 Announce Type: cross Abstract: Mathematical reasoning is essential for problem-solving in education, science, and industry, serving as a crucial benchmark for evaluating artificial

Local Ai

Mechanisms of Object Localization in Vision-Language Models

arXiv:2605.19792v1 Announce Type: new Abstract: Visually-grounded language models (VLMs) are highly effective in linking visual and textual information, yet they often struggle with basic classificati

local-aiarxiv-cs-cv

MSAVBench: Towards Comprehensive and Reliable Evaluation of Multi-Shot Audio-Video Generation

model-releasesarxiv-cs-cv

arXiv:2605.20183v1 Announce Type: new Abstract: Video generation is rapidly evolving from single-shot synthesis to complex multi-shot audio-video (MSAV) narratives to meet real-world demands. However,

Not All Tokens Are Worth Caching: Learning Semantic-Aware Eviction for LLM Prefix Caches

model-releasesarxiv-cs-lg

arXiv:2605.18825v1 Announce Type: new Abstract: Prefix caching is a key optimization in Large Language Model (LLM) serving, reusing attention Key-Value (KV) states across requests with shared prompt p

OpenCompass: A Universal Evaluation Platform for Large Language Models

arXiv:2605.19276v1 Announce Type: new Abstract: In recent years, the field of artificial intelligence has undergone a paradigm shift from task-specific small-scale models to general-purpose large lang

OpenComputer: Verifiable Software Worlds for Computer-Use Agents

arXiv:2605.19769v1 Announce Type: new Abstract: We present OpenComputer, a verifier-grounded framework for constructing verifiable software worlds for computer-use agents. OpenComputer integrates four

researcharxiv-cs-ai

PASC: Pipeline-Aware Conformal Prediction with Joint Coverage Guarantees for Multi-Stage NLP and LLM Pipelines

arXiv:2605.18812v1 Announce Type: cross Abstract: Modern NLP and LLM systems are pipelines: named entity recognition (NER) -> entity disambiguation (NED) -> entity typing, retrieval-augmented generati

agentsarxiv-cs-cl

ReacTOD: Bounded Neuro-Symbolic Agentic NLU for Zero-Shot Dialogue State Tracking

arXiv:2605.19077v1 Announce Type: cross Abstract: Task-oriented dialogue systems -- handling transactions, reservations, and service requests -- require predictable behavior, yet the moderately-sized

Robust Basis Spline Decoupling for the Compression of Transformer Models

arXiv:2605.18794v1 Announce Type: cross Abstract: Decoupling is a powerful modeling paradigm for representing multivariate functions as compositions of linear transformations and univariate nonlinear

The 99% Success Paradox: When Near-Perfect Retrieval Equals Random Selection

arXiv:2605.18857v1 Announce Type: cross Abstract: For most of the history of information retrieval (IR), search results were designed for human consumers who could scan, filter, and discard irrelevant

agentsarxiv-cs-ai

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

safetyarxiv-cs-ai

Towards Discovery of Polymers for Insulin Delivery via Physics-Grounded Agentic Workflows

arXiv:2605.18831v1 Announce Type: cross Abstract: Cold-chain storage limits access to insulin for hundreds of millions of people; a thermally protective patch polymer could help, but the design space

agentsarxiv-cs-lg

Transformers Linearly Represent Highly Structured World Models

arXiv:2605.18847v1 Announce Type: cross Abstract: Do transformers, when trained on sequential reasoning traces, build internal models of the underlying task? And if so, does the structure of those int

researcharxiv-cs-ai

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