Search: “evaluation”

Programmatic Context Augmentation for LLM-based Symbolic Regression

arXiv:2605.03101v1 Announce Type: new Abstract: Symbolic regression (SR), the task of discovering mathematical expressions that best describe a given dataset, remains a fundamental challenge in scient

researcharxiv-cs-ai

7 May 2026

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Self-Prompting Small Language Models for Privacy-Sensitive Clinical Information Extraction

DGX agent

arXiv:2605.04221v1 Announce Type: new Abstract: Clinical named entity recognition from dental progress notes is challenging because documentation is highly unstructured, domain-specific, and often pri

model-releasesarxiv-cs-cl

7 May 2026

Stream-T1: Test-Time Scaling for Streaming Video Generation

arXiv:2605.04461v1 Announce Type: new Abstract: While Test-Time Scaling (TTS) offers a promising direction to enhance video generation without the surging costs of training, current test-time video ge

tutorialsarxiv-cs-cv

7 May 2026

A Benchmark for Interactive World Models with a Unified Action Generation Framework

arXiv:2605.03941v1 Announce Type: new Abstract: Achieving Artificial General Intelligence (AGI) requires agents that learn and interact adaptively, with interactive world models providing scalable env

Safety

A Knowledge-Driven LLM-Based Decision-Support System for Explainable Defect Analysis and Mitigation Guidance in Laser Powder Bed Fusion

arXiv:2605.01100v1 Announce Type: new Abstract: This work presents a knowledge-driven decision-support system that integrates structured defect knowledge with LLM-based reasoning to provide explainabl

safetyarxiv-cs-ai

A Paradigm for Interpreting Metrics and Identifying Critical Errors in Automatic Speech Recognition

arXiv:2605.03671v1 Announce Type: new Abstract: The most commonly used metrics for evaluating automatic speech transcriptions, namely Word Error Rate (WER) and Character Error Rate (CER), have been he

researcharxiv-cs-cl

AcademiClaw: When Students Set Challenges for AI Agents

arXiv:2605.02661v1 Announce Type: new Abstract: Benchmarks within the OpenClaw ecosystem have thus far evaluated exclusively assistant-level tasks, leaving the academic-level capabilities of OpenClaw

Boundary-Aware Uncertainty Quantification for Wildfire Spread Prediction

arXiv:2605.03148v1 Announce Type: new Abstract: Reliable wildfire spread prediction is vital for risk-aware emergency planning, yet most deep learning models lack principled uncertainty quantification

researcharxiv-cs-cv

Enhancing AI-Based ECG Delineation with Deep Learning Denoising Techniques

arXiv:2605.03183v1 Announce Type: new Abstract: Evaluating canine electrocardiograms (ECGs) is challenging due to noise that can obscure clinically relevant cardiac electrical activity. Common sources

Flow Sampling: Learning to Sample from Unnormalized Densities via Denoising Conditional Processes

arXiv:2605.03984v1 Announce Type: new Abstract: Sampling from unnormalized densities is analogous to the generative modeling problem, but the target distribution is defined by a known energy function

tutorialsarxiv-cs-lg

GOAT: A Training Framework for Goal-Oriented Agent with Tools

arXiv:2510.12218v2 Announce Type: replace Abstract: Current approaches rely on zero-shot evaluation due to the absence of training data; while proprietary models such as GPT-4 exhibit strong reasoning

ISAAC: Auditing Causal Reasoning in Deep Models for Drug-Target Interaction

model-releasesarxiv-cs-lg

arXiv:2605.02962v1 Announce Type: new Abstract: Deep learning models for drug--target interaction (DTI) prediction often achieve strong benchmark performance without necessarily relying on mechanistic

LiveFMBench: Unveiling the Power and Limits of Agentic Workflows in Specification Generation

arXiv:2605.01394v1 Announce Type: cross Abstract: Formal specification is essential for rigorous program verification, yet writing correct specifications remains costly and difficult to automate. Alth

MCP-Atlas: A Large-Scale Benchmark for Tool-Use Competency with Real MCP Servers

arXiv:2602.00933v2 Announce Type: replace-cross Abstract: The Model Context Protocol (MCP) is rapidly becoming the standard interface for Large Language Models (LLMs) to discover and invoke external t

MEMSAD: Gradient-Coupled Anomaly Detection for Memory Poisoning in Retrieval-Augmented Agents

arXiv:2605.03482v1 Announce Type: cross Abstract: Persistent external memory enables LLM agents to maintain context across sessions, yet its security properties remain formally uncharacterized. We for

Multi-Agent Reasoning Improves Compute Efficiency: Pareto-Optimal Test-Time Scaling

arXiv:2605.01566v1 Announce Type: new Abstract: Advances in inference methods have enabled language models to improve their predictions without additional training. These methods often prioritize raw

PIIGuard: Mitigating PII Harvesting under Adversarial Sanitization

arXiv:2605.03129v1 Announce Type: cross Abstract: Browsing-enabled LLM assistants can fetch webpages and answer contact-seeking queries, creating a practical channel for scraping contact-style persona

Pioneering AI-assisted code migration: How Google achieved 6x faster migration from TensorFlow to JAX

model-releasesgoogle-cloud-ai

AI coding agents are rapidly becoming ubiquitous across the software industry, fundamentally changing how developers write, test, and debug daily code. While these tools excel at localized, self-conta

PriorNet: Prior-Guided Engagement Estimation from Face Video

arXiv:2605.03615v1 Announce Type: new Abstract: Engagement estimation from face video remains challenging because facial evidence is often incomplete, labeled data are limited, and engagement annotati

Applications

Robustness and Transferability of Pix2Geomodel for Bidirectional Facies Property Translation in a Complex Reservoir

arXiv:2605.03919v1 Announce Type: cross Abstract: Reservoir geomodeling is central to subsurface characterization, but it remains challenging because conditioning data are sparse, geological heterogen

applicationsarxiv-cs-cv

Scoring Edit Impact in Grammatical Error Correction via Embedded Association Graphs

arXiv:2604.06573v2 Announce Type: replace Abstract: A Grammatical Error Correction (GEC) system produces a sequence of edits to correct an erroneous sentence. The quality of these edits is typically e

researcharxiv-cs-cl

Structural Ranking of the Cognitive Plausibility of Computational Models of Analogy and Metaphors with the Minimal Cognitive Grid

arXiv:2605.01359v1 Announce Type: new Abstract: In this paper, we employ the Minimal Cognitive Grid (MCG), a framework created to evaluate the cognitive plausibility of artificial systems, to offer a

researcharxiv-cs-ai

The full Structured Output Benchmark dataset is now on @huggingface https://huggingface.co/datasets/interfaze-ai/sob

model-releasesclem-delangue--x

The Structured Output Benchmark (SOB) dataset has been released and made available on Hugging Face. This dataset, hosted by Interfaze AI, likely provides benchmark data for evaluating models' ability

Agents

WMF-AM: Probing LLM Working Memory via Depth-Parameterized Cumulative State Tracking

arXiv:2603.27343v2 Announce Type: replace Abstract: Existing large language models (LLMs) evaluations use fixed-difficulty benchmarks that cannot adapt as models improve, and rarely isolate specific c

agentsarxiv-cs-ai

A dimensional R2 regression metric

arXiv:2605.01066v1 Announce Type: new Abstract: R2 score is the standard metric for evaluating regression tasks, offering a normalized magnitude-agnostic measure of accuracy that captures variance. Ho

Applications

A Hybrid Approach for Closing the Sim2real Appearance Gap in Game Engine Synthetic Datasets

arXiv:2605.02291v1 Announce Type: new Abstract: Video game engines have been an important source for generating large volumes of visual synthetic datasets for training and evaluating computer vision a

applicationsarxiv-cs-cv

A Rational Account of Categorization Based on Information Theory

arXiv:2603.29895v2 Announce Type: replace-cross Abstract: We present a new theory of categorization based on an information-theoretic rational analysis. To evaluate this theory, we investigate how wel

ACTG-ARL: Differentially Private Conditional Text Generation with RL-Boosted Control

arXiv:2510.18232v2 Announce Type: replace Abstract: Generating high-quality synthetic text under differential privacy (DP) is critical for training and evaluating language models without compromising

Adaptation of AI-accelerated CFD Simulations to the IPU platform

arXiv:2605.00462v1 Announce Type: cross Abstract: Intelligence Processing Units (IPU) have proven useful for many AI applications. In this paper, we evaluate them within the emerging field of AI for s

tutorialsarxiv-cs-ai

Adoption and Use of LLMs at an Academic Medical Center

arXiv:2602.00074v2 Announce Type: replace-cross Abstract: While large language models (LLMs) can support clinical documentation needs, standalone tools struggle with 'workflow friction' from manual da

Local Ai

Biological Spatial Priors Regularize Foundation Model Representations for Cross-Site MSI Generalization in Colorectal Cancer

arXiv:2605.02660v1 Announce Type: cross Abstract: Predicting microsatellite instability (MSI) status from routine hematoxylin and eosin (H&E) whole slide images (WSIs) offers a practical alternative t

local-aiarxiv-cs-cv

Continual Learning of Feedback-based Molecular Communication

arXiv:2605.01020v1 Announce Type: new Abstract: This paper proposes and evaluates a new performance estimation method that leverages continual learning (CL) algorithms to carry out sequential simulati

tutorialsarxiv-cs-lg

ESARBench: A Benchmark for Agentic UAV Embodied Search and Rescue

model-releasesarxiv-cs-ro

arXiv:2605.01371v1 Announce Type: new Abstract: The rapid advancement of Multimodal Large Language Models (MLLMs) has empowered Unmanned Aerial Vehicle (UAV) with exceptional capabilities in spatial r

Grounding Synthetic Data Generation With Vision and Language Models

arXiv:2603.09625v2 Announce Type: replace Abstract: Deep learning models benefit from increasing data diversity and volume, motivating synthetic data augmentation to improve existing datasets. However

Applications

It would also be useful for funding R&D into benchmarking models, which is currently mostly done by the labs themselves right now.

applicationsethan-mollick--x

Ethan Mollick advocates for dedicated funding toward developing independent benchmarking systems for AI models, noting that evaluation is currently predominantly conducted by the labs that create the

Robustness of Transformer-Based Fluence Map Prediction Under Clinically Realistic Perturbations

arXiv:2605.00904v1 Announce Type: new Abstract: Learning-based fluence map prediction offers a fast alternative to iterative inverse planning in intensity-modulated radiation therapy (IMRT), but its r

researcharxiv-cs-cv

Social Bias in LLM-Generated Code: Benchmark and Mitigation

arXiv:2605.00382v2 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly deployed to generate code for human-centered applications where demographic fairness is critical. Howeve

Stable Localized Conformal Prediction via Transduction

arXiv:2605.01452v1 Announce Type: cross Abstract: Existing evaluations of conformal prediction, such as prediction efficiency and test-conditional coverage, are defined in expectation over the calibra

STAGE: A Full-Screenplay Benchmark for Reasoning over Evolving Storie

arXiv:2601.08510v3 Announce Type: replace Abstract: Movie screenplays are rich long-form narratives that interleave complex character relationships, temporally ordered events, and dialogue-driven inte

Submodular Benchmark Selection

model-releasesarxiv-cs-lg

arXiv:2605.02209v1 Announce Type: cross Abstract: Evaluating large language models across many benchmarks is expensive, yet many benchmarks are highly correlated. We formalize the selection of a small

TF1-EN-3M: Three Million Synthetic Moral Fables for Training Small, Open Language Models

arXiv:2504.20605v2 Announce Type: replace Abstract: Moral stories are a time-tested vehicle for transmitting values, yet modern NLP lacks a large, structured corpus that couples coherent narratives wi

The Compliance Trap: How Structural Constraints Degrade Frontier AI Metacognition Under Adversarial Pressure

arXiv:2605.02398v1 Announce Type: cross Abstract: As frontier AI models are deployed in high-stakes decision pipelines, their ability to maintain metacognitive stability -- knowing what they do not kn

Toward Culturally Grounded Natural Language Processing

arXiv:2603.26013v2 Announce Type: replace Abstract: Multilingual NLP is often treated as a route to global inclusion, but linguistic coverage and cultural competence frequently diverge. This paper syn

Toward Fine-Grained Speech Inpainting Forensics:A Dataset, Method, and Metric for Multi-Region Tampering Localization

arXiv:2605.02223v1 Announce Type: cross Abstract: Recent advances in voice cloning and text-to-speech synthesis have made partial speech manipulation - where an adversary replaces a few words within a

Towards High Fidelity Face Swapping: A Comprehensive Survey and New Benchmark

arXiv:2605.00883v1 Announce Type: new Abstract: Face swapping has witnessed significant progress in recent years, largely driven by advances in deep generative models such as GANs and diffusion models

VideoNet: A Large-Scale Dataset for Domain-Specific Action Recognition

arXiv:2605.02834v1 Announce Type: new Abstract: Videos are unique in their ability to capture actions which transcend multiple frames. Accordingly, for many years action recognition was the quintessen

A Comparative Study of QSPR Methods on a Unique Multitask PAMPA dataset

arXiv:2605.00508v1 Announce Type: new Abstract: We present a unique, multitask dataset comprising 143 drug and drug candidate molecules, each evaluated on in vitro, parallel artificial-membrane permea

4 May 2026

Local Ai

Bayesian Optimization in Linear Time