Search: “tools”

A study on a Real-Time VR-Based Teleoperation Framework for Manipulator in Dynamic Environment

arXiv:2605.30989v1 Announce Type: new Abstract: Robot teleoperation enables safe, non-contact task execution in hazardous environments where direct human access is difficult, and its application has e

safetyarxiv-cs-ro

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AI for Monitoring and Classifying Data Used in Research Literature

DGX agent

arXiv:2605.30582v1 Announce Type: new Abstract: While platforms like Google Scholar and Semantic Scholar track citations for academic papers, no comparable infrastructure exists for monitoring dataset

researcharxiv-cs-cl

1 Jun 2026

AMix-2: Establishing Protein as a Native Modality in Large Language Models

model-releasesarxiv-cs-ai

arXiv:2605.30963v1 Announce Type: cross Abstract: We present AMix-2, a protein-text foundation model that establishes protein as a native modality in large language models (LLMs), unifying protein und

Are we chasing ghosts? Quantifying unattributable polarization, and attributing the rest to annotator groups

arXiv:2602.06055v2 Announce Type: replace Abstract: Standard agreement metrics often fail to capture systematic differences in opinion between minority and majority-group annotators, jeopardizing task

researcharxiv-cs-cl

Automated Prediction of Postoperative Pancreatic Fistula Using Preoperative Computed Tomography

arXiv:2605.31539v1 Announce Type: new Abstract: Postoperative pancreatic fistula (POPF) is a serious complication after pancreatic resection, increasing morbidity, hospital stay, and healthcare costs.

Automating Formal Verification with Reinforcement Learning and Recursive Inference

arXiv:2605.30914v1 Announce Type: new Abstract: Automated formal verification remains challenging for large language models because data for proof assistants and verification-aware languages is scarce

Bifurcated Remaining Useful Life Prediction: A Hybrid Approach for Realistic Uncertainty Characterization

arXiv:2605.31241v1 Announce Type: new Abstract: This study presents a novel hybrid prognostic framework for uncertainty-aware Remaining Useful Life (RUL) estimation in turbofan engines using the NASA

Bundesrecht: An Open Library and Corpus for German Statutory Reference Processing

arXiv:2605.31338v1 Announce Type: new Abstract: Statutory references are central to legal language understanding, but are difficult to process automatically, as they appear in compact and variable sur

applicationsarxiv-cs-cl

CoFiDA-M: Concept-Aware Feature Modulation for Cross-Domain Adaptation with Image-Only Inference

arXiv:2605.31591v1 Announce Type: new Abstract: Models for AI-based skin cancer screening suffer a severe performance drop when shifting from expert dermoscopic (source) images to consumer-grade clini

Cognitive Fatigue in Autoregressive Transformers: Formalization and Measurement

arXiv:2605.30981v1 Announce Type: new Abstract: Autoregressive language models frequently degrade during long-horizon generation, producing repetitive text, losing instruction adherence, and exhibitin

applicationsarxiv-cs-cl

Combinatorial Synthesis: Scaling Code RLVR via Atomic Decomposition and Recombination

arXiv:2605.31058v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has recently emerged as the cornerstone for shaping the remarkable coding abilities of Large Langu

researcharxiv-cs-cl

Conformal C2ST: Turning weak classifiers into strong two-sample tests

arXiv:2507.17026v2 Announce Type: replace-cross Abstract: The two-sample testing problem, a fundamental task in statistics and machine learning, seeks to determine whether two sets of samples, drawn f

Cross-Modal Clinical Knowledge Integration for Mammography Report Generation

arXiv:2605.31093v1 Announce Type: new Abstract: Breast cancer is a major global health concern, and mammography screening plays a central role in early detection. The large volume of screening examina

applicationsarxiv-cs-cv

dashi: A Python library for Dataset Shift Characterization to Support Trustworthy AI Development and Deployment

arXiv:2605.31360v1 Announce Type: cross Abstract: The Artificial Intelligence (AI) life cycle requires a thorough understanding of the underlying data dynamics for robust, safe and cost-effective AI d

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories

arXiv:2602.10809v2 Announce Type: replace Abstract: Existing multimodal retrieval systems excel at semantic matching but implicitly assume that query-image relevance can be measured in isolation. This

DISCO: Mitigating Bias in Deep Learning with Conditional Distance Correlation

arXiv:2506.11653v3 Announce Type: replace-cross Abstract: Dataset bias often leads deep learning models to exploit spurious correlations instead of task-relevant signals. We introduce the Standard Ant

Discovering a Zeta Map Algorithm on Dyck Paths via Mechanistic Interpretability

arXiv:2605.30482v1 Announce Type: new Abstract: Machine learning is increasingly used in mathematical discovery, but in mathematics the desired output is often not a prediction itself, but an explicit

Discovering Differences in Strategic Behavior Between Humans and LLMs

arXiv:2602.10324v2 Announce Type: replace Abstract: As Large Language Models (LLMs) are increasingly deployed in social and strategic scenarios, it becomes critical to understand where and why their b

Do covariates explain why these groups differ? The choice of reference group can reverse conclusions in the Oaxaca-Blinder decomposition

arXiv:2603.29972v2 Announce Type: replace-cross Abstract: Scientists often want to explain why an outcome is different in two groups. For instance, differences in patient mortality rates across two ho

EGOSTREAM: A Diagnostic Benchmark for Streaming Episodic Memory in Egocentric Vision

arXiv:2605.31557v1 Announce Type: new Abstract: Continuous episodic memory is a core capability for autonomous agents operating in dynamic, real-world environments, yet current streaming video benchma

From Evidence to Design: Developing an AI-Augmented UX Research Point of View for Digital Wellbeing in Emergency and Public Safety Contexts

arXiv:2605.31146v1 Announce Type: cross Abstract: This paper investigates how User Experience Research (UXR) methods can be combined with AI-supported analysis to develop clearer design direction for

Tutorials

Function2Scene: 3D Indoor Scene Layout from Functional Specifications

arXiv:2605.30819v1 Announce Type: new Abstract: Most text-driven 3D indoor scene synthesis methods generate rooms from object-centric prompts, asking what furniture should be placed rather than how th

tutorialsarxiv-cs-cv

GGT-100K: Generative Ground Truth for Generalizable Real-World Image Restoration

arXiv:2605.31039v1 Announce Type: new Abstract: Real-world image restoration (IR) is bottlenecked by the scarcity of high-quality paired training data. Synthetic datasets are abundant but often fail t

applicationsarxiv-cs-cv

GUI-C^2: Coarse-to-Fine GUI Grounding via Difficulty-Aware Reinforcement Learning

arXiv:2605.30884v1 Announce Type: new Abstract: Existing agentic reinforcement learning methods for GUI grounding have limitations at two levels. At the data level, current approaches typically treat

HERMES: Towards Efficient and Verifiable Mathematical Reasoning in LLMs

model-releasesarxiv-cs-ai

arXiv:2511.18760v2 Announce Type: replace Abstract: Informal mathematics has been central to modern large language model (LLM) reasoning, offering flexibility and efficient construction of arguments.

How well does Classification Accuracy capture Concept Drift Detection Quality? An overview of Concept Drift Detection evaluation

arXiv:2605.31186v1 Announce Type: new Abstract: Data streams are nowadays among the most frequently analyzed data structures, with the concept drift posing a major challenge encountered by processing

Is the Last Layer Sufficient for Uncertainty Quantification?

arXiv:2605.30741v1 Announce Type: cross Abstract: Epistemic uncertainty quantification (UQ) for deep neural networks (DNNs) is a requirement for safe adoption of AI in mission-critical settings. Sever

Local Ai

iVGR: Internalizing Visually Grounded Reasoning for MLLMs with Reinforcement Learning

arXiv:2605.31096v1 Announce Type: new Abstract: While visually grounded Chain-of-Thought (CoT) has emerged as a promising paradigm to enhance fine-grained perception in multimodal large language model

local-aiarxiv-cs-cv

Kalimati Vegetable Price Index Forecasting with a Momentum Corrected Online Stacking Ensemble

arXiv:2605.30720v1 Announce Type: cross Abstract: Forecasting agricultural commodity prices in emerging economies is difficult due to high volatility, frequent supply disruptions, and strong cultural

Learning to Solve and Optimize by Evolving Code

arXiv:2605.31049v1 Announce Type: cross Abstract: Combinatorial and optimization problems are fundamental to many industrial AI applications. Solving large-scale real-world instances of such problems

applicationsarxiv-cs-ai

LH-Bench: Skill-Grounded Evaluation of Long-Horizon Agents on Subjective Enterprise Tasks

arXiv:2603.22744v2 Announce Type: replace Abstract: Large language models excel on objectively verifiable tasks such as math and programming, where evaluation reduces to unit tests or a single correct

agentsarxiv-cs-ai

Local Ai

LLM-FACETS: A Privacy-Preserving Framework for Evaluating LLM Transparency and Accountability

arXiv:2605.31167v1 Announce Type: new Abstract: Assessing whether Large Language Models outputs are factually grounded, epistemically calibrated, and methodologically reproducible is a prerequisite fo

local-aiarxiv-cs-ai

LVSA: Training-Free Sparse Attention for Long Video Diffusion

arXiv:2605.31057v1 Announce Type: new Abstract: Dense self-attention is the compute and quality bottleneck of long-video diffusion inference: cost grows quadratically with the sequence length, and bey

safetyarxiv-cs-cv

MLIPilot: LLM-Driven Auto-Research for Machine-Learned Interatomic Potentials

arXiv:2605.30889v1 Announce Type: cross Abstract: Constructing production-quality machine-learned interatomic potentials (MLIPs) requires balancing accuracy, dynamical stability, and computational thr

PASTA: A Scalable Framework for Multi-Policy AI Compliance Evaluation

arXiv:2601.11702v3 Announce Type: replace-cross Abstract: AI compliance is becoming increasingly critical as AI systems grow more powerful and pervasive. Yet the rapid expansion of AI policies creates

PictSure: Pretraining Embeddings Matters for In-Context Learning Image Classifiers

arXiv:2506.14842v2 Announce Type: replace-cross Abstract: Building image classification models remains cumbersome in data-scarce domains, where collecting large labeled datasets is impractical. In-con

agentsarxiv-cs-ai

ProofWala: A Framework for Multilingual Proof Data Synthesis and Theorem-Proving

arXiv:2502.04671v3 Announce Type: replace Abstract: Neural approaches to theorem proving require robust infrastructure for interfacing with interactive theorem provers (ITPs), extracting structured pr

Re-examining Low Rank adaptation for private LLM fine-tuning

arXiv:2510.01137v3 Announce Type: replace Abstract: Privacy is a central concern when fine-tuning large language models (LLMs) on sensitive data, and differentially private stochastic gradient descent

Separating Secrets from Placeholders: A Hybrid CNN-CodeBERT Framework for Three-Class Credential Leakage Detection

arXiv:2605.31520v1 Announce Type: cross Abstract: Credential leakage in public source code repositories poses a critical security threat, with over 23.8 million secrets exposed in 2024 alone. Existing

SPECTRA: Synthetic IR Test Collections with Relevance Oracles and Controlled Distractor Diagnostics

arXiv:2605.31575v1 Announce Type: cross Abstract: Scalable information retrieval testing needs corpora that are large enough to stress index construction, ranking latency, query routing, and evaluatio

Tutorials

Spectral Reach: Understanding Neural Scaling as Progress into the Spectral Tail

arXiv:2605.31244v1 Announce Type: new Abstract: Neural scaling laws describe predictable power-law relationships between model size, dataset size, compute, and performance. While these laws guide the

tutorialsarxiv-cs-lg

UXR PoV for Neuroinclusive Emotion Regulation

arXiv:2605.31131v1 Announce Type: cross Abstract: Attention-deficit/hyperactivity disorder (ADHD) is a psychiatric disorder which presents itself in individuals through patterns of developmentally ina

Who Gets Credit or Blame? Attributing Accountability in Modern AI Systems

arXiv:2506.00175v5 Announce Type: replace-cross Abstract: Modern AI systems are typically developed through multiple stages-pretraining, fine-tuning rounds, and subsequent adaptation or alignment, whe

Adapting Multilingual Embedding Models to Turkish via Cross-Lingual Tokenizer Surgery and Offline Distillation

model-releasesarxiv-cs-cl

arXiv:2605.29992v1 Announce Type: new Abstract: Sentence embeddings are a foundational component for semantic search, clustering, classification, and retrieval-augmented generation. This paper present

An Approach for Thyroid Nodule Analysis Using Thermographic Images

arXiv:2605.29221v1 Announce Type: new Abstract: Thyroid cancer is said to be the second most common type of cancer in female individuals and the third in males by 2030, according to projections. In ge

agentsarxiv-cs-cv

Bridging Functional and Representational Similarity via Usable Information

arXiv:2601.21568v2 Announce Type: replace Abstract: We present a unified framework for quantifying the similarity between representations through the lens of extit{usable} information, offering a rigo

CalArena: A Large-Scale Post-Hoc Calibration Benchmark

model-releasesarxiv-cs-ai

arXiv:2605.30188v1 Announce Type: cross Abstract: Reliable probability estimates are critical in many machine learning applications, yet modern classifiers are often poorly calibrated. Post-hoc calibr

Catalyst-Agent: Autonomous heterogeneous catalyst screening with an LLM Agent

arXiv:2603.01311v2 Announce Type: replace Abstract: The discovery of novel catalysts tailored for particular applications is a major challenge for the twenty-first century. Traditional methods for thi

agentsarxiv-cs-cl