Search: “evaluation”

Judge, Retrieve, or Abstain: Uncertainty-Guarded LLM Judging with Provable Risk Guarantees

arXiv:2608.17994v1 Announce Type: new Abstract: Using LLMs as judges has become standard practice for evaluating model outputs at scale. This is particularly common for subjective, open-ended tasks su

safetyarxiv-cs-cl

19 Aug 2026

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LiveHouse-TS: An Open-world Living Benchmark for Time Series Foundation Models

DGX agent

arXiv:2608.17299v1 Announce Type: new Abstract: Time Series Foundation Models (TSFMs) have recently emerged as a highly promising paradigm for cross-domain zero-shot forecasting. However, existing eva

model-releasesarxiv-cs-ai

19 Aug 2026

A Large-Scale Chinese Knowledge Graph-Text Alignment Dataset for Benchmarking Knowledge-Grounded LLMs

arXiv:2510.06039v2 Announce Type: replace-cross Abstract: Reliable evaluation of knowledge-grounded Large Language Models (LLMs) in Chinese requires resources that explicitly align Chinese-language te

18 Aug 2026

Mitigating Rubric Interference in LLM Judges via On-Policy Self-Distillation

arXiv:2608.14684v1 Announce Type: cross Abstract: LLM judges increasingly evaluate responses against fine-grained rubric checklists. When a sample requires multiple rubrics, current methods typically

18 Aug 2026

RISE: Roadside Infrastructure Sequence Understanding across 3D Tracking and Structured Vision-Language Reasoning

arXiv:2608.16480v1 Announce Type: cross Abstract: We present RISE (Roadside Infrastructure Sequence Understanding and Evaluation), a framework spanning metric 3D tracking and structured vision-languag

researcharxiv-cs-ai

18 Aug 2026

A Unified Assessment of the Poverty of the Stimulus Argument for Neural Language Models

arXiv:2602.09992v2 Announce Type: replace-cross Abstract: Several recent contributions have evaluated the Poverty of the Stimulus Hypothesis (PoSH) using Artificial Neural Networks (ANNs). The results

CFM-Bench: A Unified Multi-Domain, Multi-Task Benchmark for Channel Foundation Models

arXiv:2607.14975v2 Announce Type: replace Abstract: Channel foundation models (CFMs) are commonly evaluated in model-specific pipelines that differ in data, radio configurations, partitions, adaptatio

Do AI chatbots find what experts would? Effects of model, user role, and sample size on study retrieval for medical questions

arXiv:2608.13786v1 Announce Type: cross Abstract: Large language model (LLM) chatbots are increasingly used to answer clinical questions with citations to relevant clinical studies. Prior research has

Leading-Silence Augmentation and Multi-Stage Synthetic Supervision for the Second MLC-SLM Challenge

arXiv:2608.14150v1 Announce Type: new Abstract: The second Multilingual Conversational Speech Language Model (MLC-SLM) Challenge evaluates two tasks over complete, unsegmented multilingual conversatio

researcharxiv-cs-cl

MemoryLake on MemoryArena: A Matched Study of Agent Memory Backends

arXiv:2608.13883v1 Announce Type: new Abstract: Most agent-memory benchmarks test post-hoc recall, whereas MemoryArena evaluates whether memory supports interdependent, multi-session task completion.

CoMedBench: A Multi-Source Benchmark of Synthetic Medical Data Fidelity and Downstream Utility

model-releasesarxiv-cs-lg

arXiv:2608.12805v1 Announce Type: new Abstract: Access to clinical data is essential for developing reliable healthcare machine learning systems, but direct use of electronic health records is constra

Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization

arXiv:2608.12687v1 Announce Type: new Abstract: Bayesian optimization (BO) is a sample-efficient framework for analog circuit topology search, where evaluating each candidate topology can require cost

researcharxiv-cs-lg

H2R-Bench: Benchmarking Human-to-Robot Manipulation Video Generation in World Models

arXiv:2608.13049v1 Announce Type: cross Abstract: Large-scale manipulation data is essential for robot learning, yet collecting robot demonstrations remains expensive and difficult to scale. Meanwhile

Unified Multi-Dimensional Benchmark for Complex Graph Reasoning in Large Language Models

arXiv:2608.12391v1 Announce Type: cross Abstract: Graph reasoning provides a promising testbed for evaluating the reasoning ability of large language models (LLMs), as graph instances can be programma

Closed-Loop LLM Co-Pilots for Digital Agriculture

arXiv:2608.09949v1 Announce Type: new Abstract: This study evaluates the application of Large Language Models (LLMs) in complex biological systems, evolving from data analysis to autonomous, AI-guided

Every Token Counts: Exact Likert-Scale Distributions for Measuring LLM Attitudes and Biases

arXiv:2608.10503v1 Announce Type: new Abstract: As Large Language Models (LLMs) are increasingly deployed as autonomous agents, accurately evaluating their latent values and biases is critical. The NL

safetyarxiv-cs-cl

FADE: From Passive Verification to Active Discovery in Counterfactual Video Understanding

arXiv:2608.10764v1 Announce Type: new Abstract: Counterfactual video understanding evaluates whether models grasp physical and commonsense regularities. However, existing multiple-choice question (MCQ

How Robust Are LLMs to Vietnamese Dialects?

arXiv:2608.10414v1 Announce Type: new Abstract: Large Language Models (LLMs) are typically evaluated on standard written Vietnamese, yet everyday communication frequently involves regional dialects th

Optimize Cheap, Deploy Strong: Cost-Aware Cross-Tier Transfer for Evolutionary Optimization

arXiv:2608.10694v1 Announce Type: cross Abstract: Evolutionary optimization of LLM prompts and agentic programs (e.g., GEPA) is dominated by fitness evaluation: scoring each candidate runs an answerin

agentsarxiv-cs-ai

Back to the Future: A workbook time machine for spread sheet creation benchmarks

arXiv:2608.07873v1 Announce Type: new Abstract: We introduce the workbook time machine, a pipeline that automatically creates benchmarks evaluating the ability of language models to create derived obj

CIFA: Contextual-Intersectional Fairness Auditing for Hidden Subgroup Discovery in Face Analysis

arXiv:2608.09669v1 Announce Type: new Abstract: Fairness evaluation in computer vision commonly relies on aggregate accuracy and demographic subgroup analysis. However, visual models are also sensitiv

safetyarxiv-cs-cv

Concept-Guided Spatial Regularization for World Models in Atari Pong

arXiv:2607.15142v2 Announce Type: replace Abstract: World models are usually evaluated as components of model-based reinforcement learning (MBRL) systems, leaving their standalone reliability understu

safetyarxiv-cs-ai

Evo-Bench: Can Language Models Improve Agent Harness?

arXiv:2608.09096v1 Announce Type: new Abstract: Large Language Models (LLMs) have driven rapid progress in autonomous agents, yet standard evaluations remain confined to static task solving. An emergi

How Can Rhetoric Reward-Hack AI Reviewers? Dissecting Rhetorical Sensitivity in AI-Based Peer Review

arXiv:2608.08975v1 Announce Type: cross Abstract: As large language models increasingly participate in scientific evaluation, we investigate a potential form of reward hacking: how rhetorical choices

researcharxiv-cs-ai

LLM-Guided Heuristic Design from Simulation Traces: A Case Study in Dynamic Production and AGV Scheduling

arXiv:2608.09343v1 Announce Type: new Abstract: Simulation-based optimization (SBO) evaluates executable policies under stochastic dynamics, but most methods treat the simulator as a black box: aggreg

Mawqif-v2: An Arabic Benchmark Dataset for Cross-Target Stance Detection

arXiv:2608.09539v1 Announce Type: new Abstract: Publicly available Arabic datasets for target-specific stance detection remain limited, particularly for evaluating cross-target generalization. This pa

An End-to-End Agent Auditing Engine

arXiv:2608.07346v1 Announce Type: new Abstract: With the rapid advancement of large language models (LLMs), harnesses have become essential infrastructure for deploying agents across a wide range of d

agentsarxiv-cs-ai

10 Aug 2026

Blind to the Pivotal Vote: Aggregate Independence Metrics Miss Where Verification Actually Helps

arXiv:2608.06940v1 Announce Type: new Abstract: LLM judge panels are a standard evaluation tool, but prior work reports highly correlated panel errors: nine judges provide roughly the effective inform

safetyarxiv-cs-ai

10 Aug 2026

Applications

Can MLLMs Decode the Creative Leap? Introducing C4 for Cross-Concept Understanding

arXiv:2608.06501v1 Announce Type: new Abstract: Creative capabilities of MLLMs matter in design, communication, education, and human--AI collaboration, yet remain difficult to evaluate because explici

applicationsarxiv-cs-ai

10 Aug 2026

GAUGE: A Measurement-Grounded Benchmark for Physical Fidelity in Simulation Engines and Video World Models

arXiv:2608.05948v1 Announce Type: new Abstract: Physics engines facilitate large-scale training and evaluation for embodied intelligence, while generative video world models are emerging as implicit s

7 Aug 2026

Incident Report: unsanctioned agent behaviour during cyber testing

model-releasessimon-willison

Incident Report: unsanctioned agent behaviour during cyber testing It happened again. This time it was the UK government's AI Security Institute who accidentally attacked other companies while running

5 Aug 2026

Advancing Relevance Measurement with Vision-Language Models for Web-Scale Search

arXiv:2608.02446v1 Announce Type: cross Abstract: Relevance evaluation plays a crucial role in personalized search systems, serving as a guardrail alongside user engagement metrics to ensure that sear

safetyarxiv-cs-lg

Control Under Compression: Reliability Frontiers for Tool-Using Agents

arXiv:2608.01056v1 Announce Type: cross Abstract: Tool-using language-model agents are governed not only by task prompts but also by persistent system-side instructions that specify tools, arguments,

CrossLex: A Source-Grounded Benchmark for Cross-Jurisdictional Legal Reasoning in Large Language Models

arXiv:2608.01292v1 Announce Type: new Abstract: Legal reasoning is inherently jurisdiction-dependent: the same facts can call for different legal rules and yield different conclusions across legal sys

Don't Judge a Book by its Cover: Testing LLMs' Robustness Under Logical Obfuscation

arXiv:2602.01132v2 Announce Type: replace Abstract: Tasks such as solving arithmetic equations, evaluating truth tables, and completing syllogisms are handled well by large language models (LLMs) in t

Human-LLM Alignment in Language Attitudes Toward Non-Native Japanese

arXiv:2608.01629v1 Announce Type: new Abstract: Large language models (LLMs) increasingly evaluate human writing in high-stakes domains such as hiring and academic assessment, putting non-native speak

safetyarxiv-cs-cl

Latent-Regime Bias Auditing for Volatility Forecasting

arXiv:2608.01599v1 Announce Type: new Abstract: Volatility forecasts are commonly evaluated with aggregate accuracy metrics such as RMSE and MAE, but these metrics can hide conditional failures that m

safetyarxiv-cs-lg

WorldExam: Benchmarking World Models from Apparent Appearance to Inherent Reactivity

arXiv:2608.02603v1 Announce Type: new Abstract: Controllable video generation models are increasingly being developed as world models. Accordingly, evaluating them in this role extends beyond the appa

MerchantBench: Benchmarking LLM Agents for Long-Term Coherence in E-Commerce Operations

arXiv:2607.28956v1 Announce Type: new Abstract: Large language model agents are increasingly evaluated as autonomous tool users, yet most benchmarks focus on bounded tasks with immediate success crite

agentsarxiv-cs-ai

3 Aug 2026

Change2Task: From Repository Changes to Executable Coding Agent Tasks and Environments

arXiv:2607.28591v1 Announce Type: cross Abstract: Scaling coding agents requires a continuing supply of executable data for training, benchmarking, and continuous evaluation. Each task must couple a r

agentsarxiv-cs-cl

31 Jul 2026

PanDent: Toward Comprehensive Tooth-Level Structure-Language Consistency in Dental Radiology

arXiv:2607.27378v1 Announce Type: new Abstract: Accurate evaluation of multimodal large language models (MLLMs) in dental panoramic radiography (orthopantomogram, OPG) is limited by the lack of fine-g

31 Jul 2026

Using Large Language Models for Idea Generation in Innovation

arXiv:2607.27553v1 Announce Type: cross Abstract: This research evaluates the efficacy of large language models (LLMs) in generating new product ideas. To do so, we compare three pools of ideas for ne

31 Jul 2026

ForgetBench: Benchmarking Forgetting Dynamics of Long-Term Parametric Memory in Language Models

arXiv:2607.26455v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated strong capabilities in knowledge acquisition and reasoning, yet their ability to retain previously acquir

30 Jul 2026

SciFigQual-Bench: A Benchmark for Scientific Figure Quality Assessment with Full-Manuscript Context

arXiv:2607.27084v1 Announce Type: new Abstract: Scientific images are the core elements of presenting experimental conclusions, elaborating system architecture, and supporting comparative arguments in

30 Jul 2026

AIriskEval-edu Demo: Auditing of Pedagogical Risks in Educational Explanations

arXiv:2607.25634v1 Announce Type: new Abstract: We present AIriskEval-edu Demo, a platform that audits the pedagogical quality of instructional explanations and provides explainable audit results. The

Automate your agent development lifecycle using any coding agent

model-releasesgoogle-cloud-ai

Welcome to our latest Gemini Enterprise Agent Platform deep dive, a practical walkthrough where we’ll teach you how to build real-world, production-ready agents starting from step 1. If you haven’t al

Beyond Predictive Accuracy: A Reliability-Aware Audit of Molecular Representations for Human Olfaction

arXiv:2607.24848v1 Announce Type: cross Abstract: Pretrained molecular encoders are commonly evaluated through downstream prediction, but predictive accuracy alone does not establish that a learned re

safetyarxiv-cs-ai

From CUDA to MLX: How K-Search Brings Decades of Kernel Expertise to Apple Silicon

model-releasesberkeley-ai-research

Figure 1: CUDA-to-MLX optimization translation map. CUDA optimization knowledge can be translated into architecture-native MLX strategies rather than copied instruction-for-instruction. We face a new