Search: “tools”

Interpreto: An Explainability Library for Transformers

arXiv:2512.09730v3 Announce Type: replace Abstract: Interpreto is an open-source Python library for interpreting HuggingFace language models, from early BERT variants to LLMs. It provides two compleme

Latent Diffusion Pretraining for Crystal Property Prediction

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DGX agent

arXiv:2606.00776v1 Announce Type: new Abstract: Fast and accurate prediction of crystal properties is a central challenge in new materials design. Graph neural networks and Transformer-based models ha

local-aiarxiv-cs-lg

2 Jun 2026

Leyline: KV Cache Directives for Agentic Inference

arXiv:2606.01065v1 Announce Type: cross Abstract: Modern KV cache management assumes the chatbot workload: prompts arrive once and the cache grows append-only, so prefix caching and forward-only evict

safetyarxiv-cs-ai

Limits of Spatial Imagery Reasoning in Frontier LLM Models

arXiv:2603.26779v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have demonstrated impressive reasoning capabilities, yet they struggle with spatial tasks that require mental sim

LLM-Driven Co-Evolutionary Automated Heuristic Design for Bi-Component Coupled Combinatorial Optimization

arXiv:2606.00718v1 Announce Type: new Abstract: While Large Language Models (LLMs) have recently shown promise in Automated Heuristic Design (AHD), existing methods typically generate and evolve heuri

local-aiarxiv-cs-ai

LocalSearchBench: Benchmarking Agentic Search in Real-World Local Life Services

arXiv:2512.07436v3 Announce Type: replace Abstract: Recent advances in large reasoning models LRMs have enabled agentic search systems to perform complex multi-step reasoning across multiple sources.

LRAgent: Efficient KV Cache Sharing for Multi-LoRA LLM Agents

arXiv:2602.01053v2 Announce Type: replace Abstract: Role specialization in multi-LLM agent systems is often realized via multi-LoRA, where agents share a pretrained backbone and differ only by lightwe

agentsarxiv-cs-lg

Malaysian English News Decoded: A Linguistic Resource for Named Entity and Relation Extraction

arXiv:2402.14521v2 Announce Type: replace Abstract: Standard English and Malaysian English exhibit notable differences, posing challenges for natural language processing (NLP) tasks on Malaysian Engli

Markerless Augmented Reality Registration for Surgical Guidance: A Multi-Anatomy Clinical Accuracy Study

arXiv:2511.02086v2 Announce Type: replace Abstract: Purpose: In this paper, we develop and clinically evaluate a depth-only, markerless augmented reality (AR) registration pipeline on a head-mounted d

safetyarxiv-cs-cv

Measuring and Mitigating Bias in Code Generated by Large Language Models

arXiv:2606.00049v1 Announce Type: cross Abstract: Large language models (LLMs) are widely recognised for their applications in natural language generation and are increasingly used for code generation

Mechanistic Diagnostics of Spatial Lexical Bias in Multimodal Large Language Model Spatial Reasoning

arXiv:2606.01914v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) remain unreliable on spatial multiple-choice questions, and their failures are often attributed to poorly atten

safetyarxiv-cs-cl

Model-Native Computing Architecture: Envisioning Future System Architecture Through the Lens of Computer Architecture

arXiv:2606.00288v1 Announce Type: new Abstract: Large language models are undergoing a transition from model technology to system technology. As developers use Codex, Claude Code, AutoGPT, and related

Molecular Embedding-Based Algorithm Selection in Protein-Ligand Docking

model-releasesarxiv-cs-lg

arXiv:2512.02328v2 Announce Type: replace-cross Abstract: Selecting an effective docking algorithm is highly context-dependent, and no single method performs reliably across structural, chemical, and

On the Scaling of PEFT: Towards Million Personal Models of Trillion Parameters

model-releasesarxiv-cs-cl

arXiv:2606.02437v1 Announce Type: cross Abstract: Parameter-efficient fine-tuning (PEFT) is usually treated as a cheaper alternative to full fine-tuning. We study a broader role: small trainable adapt

OPD+: Rethinking the Advantage Design for On-Policy Distillation

arXiv:2606.01039v1 Announce Type: cross Abstract: On-policy distillation (OPD) is a widely used technique to transfer capabilities from capable teacher language models to the base student models, and

safetyarxiv-cs-ai

pcbGPT: Automatic PCB Schematic Synthesis from Natural Language Requirements

arXiv:2606.01188v1 Announce Type: cross Abstract: Translating natural-language hardware requirements into correct printed circuit board (PCB) schematics remains difficult in embedded, IoT, and wearabl

PEACE: A Planner-Executor Agent with Constraint Enforcement for UAVs

arXiv:2606.00104v1 Announce Type: cross Abstract: Foundation models are increasingly used to drive autonomous systems, yet existing approaches either keep the model in a tight control loop, raising la

local-aiarxiv-cs-ai

PINNOCHIO: Physics-Informed Neural Network for Coupled Hyperelastic Interface-Volume Simulation in Orthognathic Surgery

arXiv:2606.01572v1 Announce Type: cross Abstract: Predicting patient-specific facial soft-tissue deformation is critical for iterative orthognathic surgery planning. However, current computational met

researcharxiv-cs-cv

Quantifying the Salience of Geo-Cultural Values for Pluralistic Safety Alignment

arXiv:2606.00369v1 Announce Type: cross Abstract: Safe global deployment of AI models requires alignment with human values that vary across cultures. Yet rater pools in safety evaluation datasets rema

safetyarxiv-cs-lg

Question-Aware Evidence Ledgers for Video Relational Reasoning

model-releasesarxiv-cs-cv

arXiv:2606.02506v1 Announce Type: new Abstract: The VRR-QA challenge evaluates visual relational reasoning in videos, where answers often depend on implicit spatial relations, event boundaries, target

Relational Intervention During Functional Collapse in Large Language Models: A Lexical-Statistical Ablation and a Structure x Register Factorial

arXiv:2606.00935v1 Announce Type: new Abstract: We test whether a relational-style intervention delivered during functional collapse in a small language model produces post-collapse behavior distingui

local-aiarxiv-cs-ai

RoboBenchMart: Benchmarking Robots in Retail Environment

arXiv:2511.10276v2 Announce Type: replace-cross Abstract: Most existing robotic manipulation benchmarks focus on tabletop or household scenarios. While these setups have driven impressive progress, it

RocketSmith: An Agentic System for High-Powered Rocket Design and Manufacturing

arXiv:2606.00097v1 Announce Type: new Abstract: This work presents RocketSmith, an agentic system capable of the design, manufacturing, and optimization processes in high powered rocket development. T

agentsarxiv-cs-ro

ShapeLib: Designing a library of programmatic 3D shape abstractions with Large Language Models

arXiv:2502.08884v3 Announce Type: replace-cross Abstract: We present ShapeLib, the first method that uses the priors of Large Language Models (LLMs) to design libraries of programmatic 3D shape abstra

Statistical Guarantees for Reasoning Probes on Looped Boolean Circuits

arXiv:2602.03970v3 Announce Type: replace-cross Abstract: We study the statistical behavior of reasoning probes in a stylized model of iterative computation inspired by neural algorithmic reasoning. T

researcharxiv-cs-lg

TalkTag: Fine-Grained Morphosyntactic Error Annotation for Transcribed Speech

arXiv:2606.01820v1 Announce Type: new Abstract: Fine-grained morphosyntactic error annotation is important in clinical and developmental language research, yet it is labour-intensive, expert-dependent

TimeSage-MT: A Multi-Turn Benchmark for Evaluating Agentic Time Series Reasoning

arXiv:2606.01498v1 Announce Type: cross Abstract: Time series data inform critical decisions across many real-world domains. While large language model (LLM) agents can analyze data through natural la

Topological texture analysis of microscopy images of dynamic casein gelation and its relation to rheological properties

arXiv:2606.02048v1 Announce Type: new Abstract: We propose a novel computational toolbox that integrates Topological Data Analysis (TDA), Differential Box Counting (DBC), Multifractal Partition (MFP),

Turing Patterns for Multimedia: Reaction-Diffusion Multi-Modal Fusion for Language-Guided Video Moment Retrieval

arXiv:2606.01615v1 Announce Type: new Abstract: Video-language models are pivotal for tasks such as moment retrieval and highlight detection, yet they often struggle to capture the dynamic, non-linear

safetyarxiv-cs-cv

Uncertainty-Aware Graph Neural Reconstruction of Urban Temperature Fields from Sparse Sensors under Deployment Constraints

arXiv:2606.02038v1 Announce Type: cross Abstract: Reconstructing spatially continuous daily temperature fields from sparse observations is important for urban climate monitoring and heat-risk analysis

researcharxiv-cs-lg

Update Opacity: Epistemic Accessibility and Governance Under AI System Change

arXiv:2606.00037v1 Announce Type: cross Abstract: Machine learning models embedded in deployed AI systems are routinely updated to maintain correct functioning over time. Yet such updates can generate

safetyarxiv-cs-ai

VET: A Framework for Analyzing AI Discourse

arXiv:2606.01929v1 Announce Type: new Abstract: Public discourse on AI has become polarized; exaggerated positions on AI in traditional and social media threaten the development of AI Literacy among t

VideoBrain: Learning Adaptive Frame Sampling for Long Video Understanding

arXiv:2602.04094v2 Announce Type: replace Abstract: Long-form video understanding remains challenging for Vision-Language Models (VLMs) due to the inherent tension between computational constraints an

agentsarxiv-cs-cv

VLAMotor: Test-Guided Enhancement of Vision-Language-Action Models via Agent-BasedData Synthesis

arXiv:2606.00053v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models follow a data-driven paradigm and are constrained by the coverage of training data, making them prone to failure on

agentsarxiv-cs-ro

When Data Is Scarce: Scaling Sparse Language Models with Repeated Training

arXiv:2606.01155v1 Announce Type: cross Abstract: Scaling laws for dense LLMs under infinite data are well explored, but how sparsity interacts with limited data is not. In this work, we study sparse

When Rating Scales Fall Short: LLM-Assisted Discovery of ADHD Signals in Turkish Teacher Narratives

arXiv:2606.02509v1 Announce Type: new Abstract: Attention Deficit Hyperactivity Disorder (ADHD) is one of the most common neurodevelopmental disorders in childhood, and its diagnosis relies on assessm

Applications

WISE: A Multimodal Search Engine for Visual Scenes, Audio, Objects, Faces, Speech, and Metadata

arXiv:2602.12819v2 Announce Type: replace-cross Abstract: In this paper, we present WISE, an open-source audiovisual search engine which integrates a range of multimodal retrieval capabilities into a

applicationsarxiv-cs-cv

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

AI for Monitoring and Classifying Data Used in Research Literature

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

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

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

Automated Prediction of Postoperative Pancreatic Fistula Using Preoperative Computed Tomography

model-releasesarxiv-cs-cv

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

model-releasesarxiv-cs-lg

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

researcharxiv-cs-lg

Applications

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

model-releasesarxiv-cs-cv

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

Applications

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