{"total":74,"rows":[{"id":"2404.12272","title":"Who Validates the Validators? Aligning LLM-Assisted Evaluation of LLM Outputs with Human Preferences","created":"2024-04-18","cited_by_count":144,"area":"alignment"},{"id":"2401.06591","title":"Prometheus-Vision: Vision-Language Model as a Judge for Fine-Grained Evaluation","created":"2024-01-12","cited_by_count":125,"area":"mllm"},{"id":"2407.04069","title":"A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendations","created":"2024-07-04","cited_by_count":85,"area":null},{"id":"2402.01383","title":"LLM-based NLG Evaluation: Current Status and Challenges","created":"2024-02-02","cited_by_count":73,"area":null},{"id":"2407.00870","title":"Roleplay-doh: Enabling Domain-Experts to Create LLM-simulated Patients via Eliciting and Adhering to Principles","created":"2024-07-01","cited_by_count":73,"area":null},{"id":"2503.02068","title":"Interactive Debugging and Steering of Multi-Agent AI Systems","created":"2025-03-03","cited_by_count":68,"area":"agents"},{"id":"2402.10294","title":"LAVE: LLM-Powered Agent Assistance and Language Augmentation for Video Editing","created":"2024-02-15","cited_by_count":47,"area":"agents"},{"id":"2401.07103","title":"Leveraging Large Language Models for NLG Evaluation: Advances and Challenges","created":"2024-01-13","cited_by_count":37,"area":null},{"id":"2402.12055","title":"Are LLM-based Evaluators Confusing NLG Quality Criteria?","created":"2024-02-19","cited_by_count":36,"area":null},{"id":"2405.10313","title":"How Far Are We From AGI: Are LLMs All We Need?","created":"2024-05-16","cited_by_count":31,"area":null},{"id":"2402.10524","title":"LLM Comparator: Visual Analytics for Side-by-Side Evaluation of Large Language Models","created":"2024-02-16","cited_by_count":29,"area":null},{"id":"2407.02397","title":"Learning to Refine with Fine-Grained Natural Language Feedback","created":"2024-07-02","cited_by_count":27,"area":null},{"id":"2410.04078","title":"TeachTune: Reviewing Pedagogical Agents Against Diverse Student Profiles with Simulated Students","created":"2024-10-05","cited_by_count":25,"area":"agents"},{"id":"2409.08775","title":"What Should We Engineer in Prompts? Training Humans in Requirement-Driven LLM Use","created":"2024-09-13","cited_by_count":24,"area":null},{"id":"2508.01674","title":"CUPID: Evaluating Personalized and Contextualized Alignment of LLMs from Interactions","created":"2025-08-03","cited_by_count":22,"area":null},{"id":"2401.03038","title":"SPADE: Synthesizing Data Quality Assertions for Large Language Model Pipelines","created":"2024-01-05","cited_by_count":19,"area":"synth"},{"id":"2402.08855","title":"GhostWriter: Augmenting Collaborative Human-AI Writing Experiences Through Personalization and Agency","created":"2024-02-13","cited_by_count":18,"area":null},{"id":"2406.09264","title":"Position: Towards Bidirectional Human-AI Alignment","created":"2024-06-13","cited_by_count":18,"area":"alignment"},{"id":"2408.14622","title":"What Makes a Good Story and How Can We Measure It? A Comprehensive Survey of Story Evaluation","created":"2024-08-26","cited_by_count":17,"area":null},{"id":"2501.12557","title":"Understanding the LLM-ification of CHI: Unpacking the Impact of LLMs at CHI through a Systematic Literature Review","created":"2025-01-22","cited_by_count":16,"area":null},{"id":"2503.12651","title":"VeriLA: A Human-Centered Evaluation Framework for Interpretable Verification of LLM Agent Failures","created":"2025-03-16","cited_by_count":14,"area":"agents"},{"id":"2410.12071","title":"Beyond the Comfort Zone: Emerging Solutions to Overcome Challenges in Integrating LLMs into Software Products","created":"2024-10-15","cited_by_count":11,"area":null},{"id":"2504.07971","title":"SPHERE: An Evaluation Card for Human-AI Systems","created":"2025-03-24","cited_by_count":9,"area":null},{"id":"2405.05418","title":"Mitigating Exaggerated Safety in Large Language Models","created":"2024-05-08","cited_by_count":8,"area":null},{"id":"2510.14591","title":"Just-In-Time Objectives: A General Approach for Specialized AI Interactions","created":"2025-10-16","cited_by_count":7,"area":null},{"id":"2602.05446","title":"DiLLS: Interactive Diagnosis of LLM-based Multi-agent Systems via Layered Summary of Agent Behaviors","created":"2026-02-05","cited_by_count":7,"area":"agents"},{"id":"2409.13588","title":"ChainBuddy: An AI Agent System for Generating LLM Pipelines","created":"2024-09-20","cited_by_count":6,"area":"agents"},{"id":"2410.18652","title":"$C^2$: Scalable Auto-Feedback for LLM-based Chart Generation","created":"2024-10-24","cited_by_count":6,"area":null},{"id":"2504.14738","title":"PROMPTEVALS: A Dataset of Assertions and Guardrails for Custom Production Large Language Model Pipelines","created":"2025-04-20","cited_by_count":6,"area":"safety"},{"id":"2405.03845","title":"Self-Improving Customer Review Response Generation Based on LLMs","created":"2024-05-06","cited_by_count":5,"area":"synth"},{"id":"2409.18203","title":"Policy Maps: Tools for Guiding the Unbounded Space of LLM Behaviors","created":"2024-09-26","cited_by_count":5,"area":null},{"id":"2503.23730","title":"KOFFVQA: An Objectively Evaluated Free-form VQA Benchmark for Large Vision-Language Models in the Korean Language","created":"2025-03-31","cited_by_count":5,"area":"mllm"},{"id":"2604.10925","title":"From Words to Widgets for Controllable LLM Generation","created":"2026-04-13","cited_by_count":5,"area":null},{"id":"2404.11072","title":"Large Language Models Meet User Interfaces: The Case of Provisioning Feedback","created":"2024-04-17","cited_by_count":4,"area":null},{"id":"2407.18376","title":"Exploring Bengali Religious Dialect Biases in Large Language Models with Evaluation Perspectives","created":"2024-07-25","cited_by_count":4,"area":null},{"id":"2503.05039","title":"Bridging the AI Adoption Gap: Designing an Interactive Pedagogical Agent for Higher Education Instructors","created":"2025-03-06","cited_by_count":4,"area":"agents"},{"id":"2506.14200","title":"ELI-Why: Evaluating the Pedagogical Utility of Language Model Explanations","created":"2025-06-17","cited_by_count":4,"area":null},{"id":"2508.06056","title":"RAGTrace: Understanding and Refining Retrieval-Generation Dynamics in Retrieval-Augmented Generation","created":"2025-08-08","cited_by_count":4,"area":"rag"},{"id":"2507.18802","title":"DxHF: Providing High-Quality Human Feedback for LLM Alignment via Interactive Decomposition","created":"2025-07-24","cited_by_count":3,"area":"alignment"},{"id":"2507.23453","title":"Counterfactual Evaluation for Blind Attack Detection in LLM-based Evaluation Systems","created":"2025-07-31","cited_by_count":3,"area":"safety"},{"id":"2508.12555","title":"Illuminating LLM Coding Agents: Visual Analytics for Deeper Understanding and Enhancement","created":"2025-08-18","cited_by_count":3,"area":"agents"},{"id":"2509.11206","title":"Evalet: Evaluating Large Language Models through Functional Fragmentation","created":"2025-09-14","cited_by_count":3,"area":null},{"id":"2408.04560","title":"Conversational Prompt Engineering","created":"2024-08-08","cited_by_count":2,"area":null},{"id":"2507.09037","title":"ALIGN: Prompt-based Attribute Alignment for Reliable, Responsible, and Personalized LLM-based Decision-Making","created":"2025-07-11","cited_by_count":2,"area":null},{"id":"2508.08504","title":"When the Domain Expert Has No Time and the LLM Developer Has No Clinical Expertise: Real-World Lessons from LLM Co-Design in a Safety-Net Hospital","created":"2025-08-11","cited_by_count":2,"area":null},{"id":"2510.06872","title":"Prototyping Multimodal GenAI Real-Time Agents with Counterfactual Replays and Hybrid Wizard-of-Oz","created":"2025-10-08","cited_by_count":2,"area":"agents"},{"id":"2510.08120","title":"Interpreting LLM-as-a-Judge Policies via Verifiable Global Explanations","created":"2025-10-09","cited_by_count":2,"area":null},{"id":"2511.04478","title":"Generate, Evaluate, Iterate: Synthetic Data for Human-in-the-Loop Refinement of LLM Judges","created":"2025-11-06","cited_by_count":2,"area":"synth"},{"id":"2603.00057","title":"\"Bespoke Bots\": Diverse Instructor Needs for Customizing Generative AI Classroom Chatbots","created":"2026-02-10","cited_by_count":2,"area":null},{"id":"2604.21769","title":"Who Defines \"Best\"? Towards Interactive, User-Defined Evaluation of LLM Leaderboards","created":"2026-04-23","cited_by_count":2,"area":null},{"id":"2406.03843","title":"POEM: Interactive Prompt Optimization for Enhancing Multimodal Reasoning of Large Language Models","created":"2024-06-06","cited_by_count":1,"area":"lr"},{"id":"2501.15727","title":"Gensors: Authoring Personalized Visual Sensors with Multimodal Foundation Models and Reasoning","created":"2025-01-27","cited_by_count":1,"area":"lr"},{"id":"2505.07664","title":"A Case Study Investigating the Role of Generative AI in Quality Evaluations of Epics in Agile Software Development","created":"2025-05-12","cited_by_count":1,"area":null},{"id":"2507.17264","title":"Understanding Prompt Programming Tasks and Questions","created":"2025-07-23","cited_by_count":1,"area":null},{"id":"2510.12728","title":"Data-Prompt Co-Evolution: Growing Test Sets to Refine LLM Behavior","created":"2025-10-14","cited_by_count":1,"area":null},{"id":"2602.14357","title":"Key Considerations for Domain Expert Involvement in LLM Design and Evaluation: An Ethnographic Study","created":"2026-02-16","cited_by_count":1,"area":null},{"id":"2602.21059","title":"An Expert Schema for Evaluating Large Language Model Errors in Scholarly Question-Answering Systems","created":"2026-02-24","cited_by_count":1,"area":null},{"id":"2603.05832","title":"Lexara: A User-Centered Toolkit for Evaluating Large Language Models for Conversational Visual Analytics","created":"2026-03-06","cited_by_count":1,"area":null},{"id":"2604.00022","title":"Criterion Validity of LLM-as-Judge for Business Outcomes in Conversational Commerce","created":"2026-03-11","cited_by_count":1,"area":null},{"id":"2608.12097","title":"Graph-Structured Rubrics: Compiling Rubrics into Typed Evaluation Graphs for LLM Judges","created":"2026-08-12","cited_by_count":1,"area":null},{"id":"2506.21582","title":"VIDEE: Visual and Interactive Decomposition, Execution, and Evaluation of Text Analytics with Intelligent Agents","created":"2025-06-17","cited_by_count":0,"area":"agents"},{"id":"2509.19680","title":"PolicyPad: Collaborative Prototyping of LLM Policies","created":"2025-09-24","cited_by_count":0,"area":null},{"id":"2512.10234","title":"InFerActive: Interactive Tree-Based Exploration of LLM Sampling for Safety Evaluation","created":"2025-12-11","cited_by_count":0,"area":null},{"id":"2604.14137","title":"From Feelings to Metrics: Understanding and Formalizing How Users Vibe-Test LLMs","created":"2026-04-15","cited_by_count":0,"area":null},{"id":"2605.06054","title":"Visual Fingerprints for LLM Generation Comparison","created":"2026-05-07","cited_by_count":0,"area":null},{"id":"2605.20149","title":"Less Back-and-Forth: A Comparative Study of Structured Prompting","created":"2026-05-19","cited_by_count":0,"area":null},{"id":"2607.12193","title":"Compos3D: Interactive Part-Based Composition for Creative Control in Generative 3D Models","created":"2026-07-13","cited_by_count":0,"area":null},{"id":"2608.28534","title":"InstructMesh: Selective Refinement of Generative 3D Models for Fabrication","created":"2026-08-28","cited_by_count":0,"area":null},{"id":"2609.10385","title":"MOONWALK: Mediating Operations with Intent-Evidence-Action Alignment Across Junior-Supervisor Review Workflows in Animation/VFX Pre-Production","created":"2026-09-09","cited_by_count":0,"area":null},{"id":"2609.22097","title":"Token Signatures of Code: Comparing Coding Behaviors Across Large Language Models","created":"2026-08-12","cited_by_count":0,"area":null},{"id":"2609.32092","title":"On Evaluating and Improving Conversational Agents in Production","created":"2026-09-25","cited_by_count":0,"area":"agents"},{"id":"2609.35804","title":"Evaluating the Effects of Prompt Perturbation on Bias and Hallucination in Large Language Models","created":"2026-09-18","cited_by_count":0,"area":null},{"id":"2609.35815","title":"How to Run Statistics over LLM Judges and Trust the Results: Calibrated Inference for Small-Sample AI Evaluation with evalstats","created":"2026-09-20","cited_by_count":0,"area":null},{"id":"2609.40103","title":"JuryFlow: Disagreement-Guided Human-in-the-Loop Multi-Agent Evaluation","created":"2026-09-30","cited_by_count":0,"area":"agents"}],"next_cursor":null}