Search: “evaluation”

Purging the Gray Zone: Latent-Geometric Denoising for Precise Knowledge Boundary Awareness

arXiv:2604.14324v1 Announce Type: new Abstract: Large language models (LLMs) often exhibit hallucinations due to their inability to accurately perceive their own knowledge boundaries. Existing abstent

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Quantization of Spiking Neural Networks Beyond Accuracy

DGX agent

arXiv:2604.14487v1 Announce Type: new Abstract: Quantization is a natural complement to the sparse, event-driven computation of Spiking Neural Networks, reducing memory bandwidth and arithmetic cost f

researcharxiv-cs-lg

17 Apr 2026

Route to Rome Attack: Directing LLM Routers to Expensive Models via Adversarial Suffix Optimization

arXiv:2604.15022v1 Announce Type: cross Abstract: Cost-aware routing dynamically dispatches user queries to models of varying capability to balance performance and inference cost. However, the routing

Scouting By Reward: VLM-TO-IRL-Driven Player Selection For Esports

arXiv:2604.14474v1 Announce Type: new Abstract: Traditional esports scouting workflows rely heavily on manual video review and aggregate performance metrics, which often fail to capture the nuanced de

safetyarxiv-cs-lg

Secure and Privacy-Preserving Vertical Federated Learning

model-releasesarxiv-cs-ai

arXiv:2604.13474v1 Announce Type: cross Abstract: We propose a novel end-to-end privacy-preserving framework, instantiated by three efficient protocols for different deployment scenarios, covering bot

Shapley Value-Guided Adaptive Ensemble Learning for Explainable Financial Fraud Detection with U.S. Regulatory Compliance Validation

arXiv:2604.14231v1 Announce Type: new Abstract: Financial crime costs U.S. institutions over $32 billion each year. Although AI tools for fraud detection have become more advanced, their use in real-w

applicationsarxiv-cs-lg

StreamCacheVGGT: Streaming Visual Geometry Transformers with Robust Scoring and Hybrid Cache Compression

arXiv:2604.15237v1 Announce Type: new Abstract: Reconstructing dense 3D geometry from continuous video streams requires stable inference under a constant memory budget. Existing O(1) frameworks primar

researcharxiv-cs-cv

Style Amnesia: Investigating Speaking Style Degradation and Mitigation in Multi-Turn Spoken Language Models

arXiv:2512.23578v3 Announce Type: replace Abstract: In this paper, we show that when spoken language models (SLMs) are instructed to speak in a specific speaking style at the beginning of a multi-turn

researcharxiv-cs-cl

TennisTV: Do Multimodal Large Language Models Understand Tennis Rallies?

arXiv:2509.15602v5 Announce Type: replace Abstract: Multimodal large language models (MLLMs) excel at general video understanding but struggle with fast, high-frequency sports like tennis, where rally

The Fourth Challenge on Image Super-Resolution (imes4) at NTIRE 2026: Benchmark Results and Method Overview

arXiv:2604.14558v1 Announce Type: new Abstract: This paper presents the NTIRE 2026 image super-resolution (imes4) challenge, one of the associated competitions of the NTIRE 2026 Workshop at CVPR 2026.

The PICCO Framework for Large Language Model Prompting: A Taxonomy and Reference Architecture for Prompt Structure

arXiv:2604.14197v1 Announce Type: new Abstract: Large language model (LLM) performance depends heavily on prompt design, yet prompt construction is often described and applied inconsistently. Our purp

safetyarxiv-cs-cl

Theory of Mind in Action: The Instruction Inference Task in Dynamic Human-Agent Collaboration

arXiv:2507.02935v2 Announce Type: replace Abstract: Successful human-agent teaming relies on an agent being able to understand instructions given by a (human) principal. In many cases, an instruction

Local Ai

Tight Sample Complexity Bounds for Best-Arm Identification Under Bounded Systematic Bias

arXiv:2604.14345v1 Announce Type: new Abstract: As search depth increases in autonomous reasoning and embodied planning, the candidate action space expands exponentially, heavily taxing computational

local-aiarxiv-cs-lg

Trust and Reliance on AI in Education: AI Literacy and Need for Cognition as Moderators

arXiv:2604.01114v2 Announce Type: replace-cross Abstract: As generative AI systems are integrated into educational settings, students often encounter AI-generated output while working through learning

applicationsarxiv-cs-ai

Tutorials

World-Value-Action Model: Implicit Planning for Vision-Language-Action Systems

arXiv:2604.14732v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have emerged as a promising paradigm for building embodied agents that ground perception and language into action.

tutorialsarxiv-cs-lg

WybeCoder: Verified Imperative Code Generation

arXiv:2603.29088v2 Announce Type: replace-cross Abstract: Recent progress in large language models (LLMs) has substantially advanced automatic code generation and formal theorem proving, yet software

agentsarxiv-cs-ai

🇺🇸 xAI just dropped a real-time speech-to-text model built for voice apps: high limits, multi-language support, the works. Priced at just …

model-releaseselon-musk--x

🇺🇸 xAI just dropped a real-time speech-to-text model built for voice apps: high limits, multi-language support, the works. Priced at just 0.10–0.20/hour, crushing most competitors. Quiet release, loud

Zero-Shot Retail Theft Detection via Orchestrated Vision Models: A Model-Agnostic, Cost-Effective Alternative to Trained Single-Model Systems

arXiv:2604.14846v1 Announce Type: new Abstract: Retail theft costs the global economy over 100 billion annually, yet existing AI-based detection systems require expensive custom model training on prop

A Bayesian Framework for Uncertainty-Aware Explanations in Power Quality Disturbance Classification

arXiv:2604.13658v1 Announce Type: new Abstract: Advanced deep learning methods have shown remarkable success in power quality disturbance (PQD) classification. To enhance model transparency, explainab

safetyarxiv-cs-lg

Adaptive Conformal Prediction for Improving Factuality of Generations by Large Language Models

arXiv:2604.13991v1 Announce Type: new Abstract: Large language models (LLMs) are prone to generating factually incorrect outputs. Recent work has applied conformal prediction to provide uncertainty es

researcharxiv-cs-cl

AeTHERON: Autoregressive Topology-aware Heterogeneous Graph Operator Network for Fluid-Structure Interaction

arXiv:2604.13369v1 Announce Type: cross Abstract: Surrogate modeling of body-driven fluid flows where immersed moving boundaries couple structural dynamics to chaotic, unsteady fluid phenomena remains

AI Powered Image Analysis for Phishing Detection

arXiv:2604.13555v1 Announce Type: new Abstract: Phishing websites now rely heavily on visual imitation-copied logos, similar layouts, and matching colours-to avoid detection by text- and URL-based sys

Auto-FP: An Experimental Study of Automated Feature Preprocessing for Tabular Data

arXiv:2310.02540v2 Announce Type: replace Abstract: Classical machine learning models, such as linear models and tree-based models, are widely used in industry. These models are sensitive to data dist

Bi-Predictability: A Real-Time Signal for Monitoring LLM Interaction Integrity

arXiv:2604.13061v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in high-stakes autonomous and interactive workflows, where reliability demands continuous, multi-

agentsarxiv-cs-cl

Can Coding Agents Be General Agents?

arXiv:2604.13107v1 Announce Type: cross Abstract: As coding agents have seen rapid capability and adoption gains, users are applying them to general tasks beyond software engineering. In this post, we

agentsarxiv-cs-lg

Co-FactChecker: A Framework for Human-AI Collaborative Claim Verification Using Large Reasoning Models

arXiv:2604.13706v1 Announce Type: new Abstract: Professional fact-checkers rely on domain knowledge and deep contextual understanding to verify claims. Large language models (LLMs) and large reasoning

agentsarxiv-cs-cl

CodeFlowBench: A Multi-turn, Iterative Benchmark for Complex Code Generation

arXiv:2504.21751v4 Announce Type: replace-cross Abstract: Modern software development demands code that is maintainable, testable, and scalable by organizing the implementation into modular components

Common to Whom? Regional Cultural Commonsense and LLM Bias in India

arXiv:2601.15550v3 Announce Type: replace Abstract: Existing cultural commonsense benchmarks treat nations as monolithic, assuming uniform practices within national boundaries. But does cultural commo

Concrete Jungle: Towards Concreteness Paved Contrastive Negative Mining for Compositional Understanding

arXiv:2604.13313v1 Announce Type: new Abstract: Vision-Language Models demonstrate remarkable capabilities but often struggle with compositional reasoning, exhibiting vulnerabilities regarding word or

researcharxiv-cs-lg

Counterfactual Peptide Editing for Causal TCR--pMHC Binding Inference

arXiv:2604.13256v1 Announce Type: new Abstract: Neural models for TCR-pMHC binding prediction are susceptible to shortcut learning: they exploit spurious correlations in training data -- such as pepti

Diagnostics for Individual-Level Prediction Instability in Machine Learning for Healthcare

arXiv:2603.00192v2 Announce Type: replace Abstract: In healthcare, predictive models increasingly inform patient-level decisions, yet little attention is paid to the variability in individual risk est

applicationsarxiv-cs-lg

EMGFlow: Robust and Efficient Surface Electromyography Synthesis via Flow Matching

arXiv:2604.13685v1 Announce Type: cross Abstract: Deep learning-based surface electromyography (sEMG) gesture recognition is frequently bottlenecked by data scarcity and limited subject diversity. Whi

Estimating Continuous Treatment Effects with Two-Stage Kernel Ridge Regression

arXiv:2604.13410v1 Announce Type: cross Abstract: We study the problem of estimating the effect function for a continuous treatment, which maps each treatment value to a population-averaged outcome. A

safetyarxiv-cs-lg

Feed-Forward 3D Scene Modeling: A Problem-Driven Perspective

arXiv:2604.14025v1 Announce Type: new Abstract: Reconstructing 3D representations from 2D inputs is a fundamental task in computer vision and graphics, serving as a cornerstone for understanding and i

applicationsarxiv-cs-cv

From Relevance to Authority: Authority-aware Generative Retrieval in Web Search Engines

arXiv:2604.13468v1 Announce Type: cross Abstract: Generative information retrieval (GenIR) formulates the retrieval process as a text-to-text generation task, leveraging the vast knowledge of large la

GeoVision-Enabled Digital Twin for Hybrid Autonomous-Teleoperated Medical Responses

arXiv:2604.13248v1 Announce Type: new Abstract: Remote medical response systems are increasingly being deployed to support emergency care in disaster-affected and infrastructure-limited environments.

agentsarxiv-cs-ro

Getting the Numbers Rightnicode{x2014}Modelling Multi-Class Object Counting in Dense and Varied Scenes

arXiv:2510.02213v2 Announce Type: replace Abstract: Density map estimation enables accurate object counting in heavily occluded, and densely packed scenes where detection-based counting fails. In mult

researcharxiv-cs-cv

Graph Propagated Projection Unlearning: A Unified Framework for Vision and Audio Discriminative Models

arXiv:2604.13127v1 Announce Type: new Abstract: The need to selectively and efficiently erase learned information from deep neural networks is becoming increasingly important for privacy, regulatory c

researcharxiv-cs-cv

Hessian-Enhanced Token Attribution (HETA): Interpreting Autoregressive LLMs

arXiv:2604.13258v1 Announce Type: new Abstract: Attribution methods seek to explain language model predictions by quantifying the contribution of input tokens to generated outputs. However, most exist

IWLV-Ramayana: A Sarga-Aligned Parallel Corpus of Valmiki's Ramayana Across Indian Languages

arXiv:2604.13078v1 Announce Type: new Abstract: The Ramayana is among the most influential literary traditions of South and Southeast Asia, transmitted across numerous linguistic and cultural contexts

Just Use XML: Revisiting Joint Translation and Label Projection

arXiv:2603.12021v2 Announce Type: replace Abstract: Label projection is an effective technique for cross-lingual transfer, extending span-annotated datasets from a high-resource language to low-resour

researcharxiv-cs-cl

Learning-Based Estimation of Spatially Resolved Scatter Radiation Fields in Interventional Radiology

arXiv:2512.17654v3 Announce Type: replace Abstract: We present three variants of a lightweight, fully connected artificial neural network, suited for interactive estimation of three-dimensional, spati

researcharxiv-cs-lg

LiteParse should be the default document parser you use with any AI agent (Claude Code, Claude Cowork, OpenClaw, Codex, and more) The core i…

model-releasesjerry-liu--x

LiteParse should be the default document parser you use with any AI agent (Claude Code, Claude Cowork, OpenClaw, Codex, and more) The core is extremely fast text and accurate parsing from any document

Logical Phase Transitions: Understanding Collapse in LLM Logical Reasoning

arXiv:2601.02902v2 Announce Type: replace-cross Abstract: Symbolic logical reasoning is a critical yet underexplored capability of large language models (LLMs), providing reliable and verifiable decis

Local Ai

Multi-Agent Object Detection Framework Based on Raspberry Pi YOLO Detector and Slack-Ollama Natural Language Interface

arXiv:2604.13345v1 Announce Type: new Abstract: The paper presents design and prototype implementation of an edge based object detection system within the new paradigm of AI agents orchestration. It g

local-aiarxiv-cs-cv

Optimization with SpotOptim

arXiv:2604.13672v1 Announce Type: new Abstract: The `spotoptim` package implements surrogate-model-based optimization of expensive black-box functions in Python. Building on two decades of Sequential

Out of Context: Reliability in Multimodal Anomaly Detection Requires Contextual Inference

arXiv:2604.13252v1 Announce Type: new Abstract: Anomaly detection aims to identify observations that deviate from expected behavior. Because anomalous events are inherently sparse, most frameworks are

Peer-Predictive Self-Training for Language Model Reasoning

arXiv:2604.13356v1 Announce Type: new Abstract: Mechanisms for continued self-improvement of language models without external supervision remain an open challenge. We propose Peer-Predictive Self-Trai