{"total":131,"rows":[{"id":"2411.16594","title":"From Generation to Judgment: Opportunities and Challenges of LLM-as-a-judge","created":"2024-11-25","cited_by_count":494,"area":null},{"id":"2404.13781","title":"Evaluating Retrieval Quality in Retrieval-Augmented Generation","created":"2024-04-21","cited_by_count":90,"area":"rag"},{"id":"2501.00274","title":"LLM-Rubric: A Multidimensional, Calibrated Approach to Automated Evaluation of Natural Language Texts","created":"2024-12-31","cited_by_count":87,"area":null},{"id":"2410.05440","title":"Can LLMs Understand Time Series Anomalies?","created":"2024-10-07","cited_by_count":41,"area":null},{"id":"2508.20033","title":"DeepScholar-Bench: A Live Benchmark and Automated Evaluation for Generative Research Synthesis","created":"2025-08-27","cited_by_count":34,"area":null},{"id":"2402.17826","title":"Prediction-Powered Ranking of Large Language Models","created":"2024-02-27","cited_by_count":29,"area":null},{"id":"2402.09543","title":"Rethinking Large Language Model Architectures for Sequential Recommendations","created":"2024-02-14","cited_by_count":27,"area":"lr"},{"id":"2403.12173","title":"TnT-LLM: Text Mining at Scale with Large Language Models","created":"2024-03-18","cited_by_count":26,"area":null},{"id":"2505.01976","title":"A Survey on Privacy Risks and Protection in Large Language Models","created":"2025-05-04","cited_by_count":21,"area":"safety"},{"id":"2409.16022","title":"AI Can Be Cognitively Biased: An Exploratory Study on Threshold Priming in LLM-Based Batch Relevance Assessment","created":"2024-09-24","cited_by_count":20,"area":null},{"id":"2505.04847","title":"Benchmarking LLM Faithfulness in RAG with Evolving Leaderboards","created":"2025-05-07","cited_by_count":20,"area":"rag"},{"id":"2311.09812","title":"Large Language Models for Propaganda Span Annotation","created":"2023-11-16","cited_by_count":19,"area":null},{"id":"2402.04678","title":"FaithLM: Towards Faithful Explanations for Large Language Models","created":"2024-02-07","cited_by_count":19,"area":null},{"id":"2402.11891","title":"FeB4RAG: Evaluating Federated Search in the Context of Retrieval Augmented Generation","created":"2024-02-19","cited_by_count":19,"area":"rag"},{"id":"2405.07767","title":"Synthetic Test Collections for Retrieval Evaluation","created":"2024-05-13","cited_by_count":19,"area":null},{"id":"2404.01012","title":"Query Performance Prediction using Relevance Judgments Generated by Large Language Models","created":"2024-04-01","cited_by_count":18,"area":null},{"id":"2411.08275","title":"A Large-Scale Study of Relevance Assessments with Large Language Models: An Initial Look","created":"2024-11-13","cited_by_count":18,"area":null},{"id":"2412.10047","title":"Large Action Models: From Inception to Implementation","created":"2024-12-13","cited_by_count":18,"area":null},{"id":"2402.18031","title":"Corpus-Steered Query Expansion with Large Language Models","created":"2024-02-28","cited_by_count":17,"area":null},{"id":"2405.05600","title":"Can We Use Large Language Models to Fill Relevance Judgment Holes?","created":"2024-05-09","cited_by_count":17,"area":null},{"id":"2408.15836","title":"Knowledge Navigator: LLM-guided Browsing Framework for Exploratory Search in Scientific Literature","created":"2024-08-28","cited_by_count":17,"area":null},{"id":"2410.08601","title":"StraGo: Harnessing Strategic Guidance for Prompt Optimization","created":"2024-10-11","cited_by_count":17,"area":null},{"id":"2501.04410","title":"User Simulation in the Era of Generative AI: User Modeling, Synthetic Data Generation, and System Evaluation","created":"2025-01-08","cited_by_count":17,"area":null},{"id":"2403.18405","title":"Leveraging Large Language Models for Relevance Judgments in Legal Case Retrieval","created":"2024-03-27","cited_by_count":16,"area":null},{"id":"2503.19092","title":"Rankers, Judges, and Assistants: Towards Understanding the Interplay of LLMs in Information Retrieval Evaluation","created":"2025-03-24","cited_by_count":15,"area":null},{"id":"2504.12408","title":"A Human-AI Comparative Analysis of Prompt Sensitivity in LLM-Based Relevance Judgment","created":"2025-04-16","cited_by_count":15,"area":null},{"id":"2504.13128","title":"FreshStack: Building Realistic Benchmarks for Evaluating Retrieval on Technical Documents","created":"2025-04-17","cited_by_count":15,"area":null},{"id":"2311.01235","title":"Advancing the Search Frontier with AI Agents","created":"2023-11-02","cited_by_count":12,"area":null},{"id":"2401.04122","title":"From Prompt Engineering to Prompt Science With Human in the Loop","created":"2024-01-01","cited_by_count":12,"area":null},{"id":"2401.17435","title":"Can LLMs Replace Economic Choice Prediction Labs? The Case of Language-based Persuasion Games","created":"2024-01-30","cited_by_count":12,"area":null},{"id":"2409.11860","title":"Retrieve, Annotate, Evaluate, Repeat: Leveraging Multimodal LLMs for Large-Scale Product Retrieval Evaluation","created":"2024-09-18","cited_by_count":12,"area":"mllm"},{"id":"2412.13102","title":"AIR-Bench: Automated Heterogeneous Information Retrieval Benchmark","created":"2024-12-17","cited_by_count":12,"area":null},{"id":"2406.14783","title":"Evaluating RAG-Fusion with RAGElo: an Automated Elo-based Framework","created":"2024-06-20","cited_by_count":11,"area":"rag"},{"id":"2410.08696","title":"AMPO: Automatic Multi-Branched Prompt Optimization","created":"2024-10-11","cited_by_count":11,"area":null},{"id":"2311.07930","title":"It's All Relative! -- A Synthetic Query Generation Approach for Improving Zero-Shot Relevance Prediction","created":"2023-11-14","cited_by_count":10,"area":null},{"id":"2604.16706","title":"Auditing Automated Evaluation, Error Propagation, and Runtime Mitigation in Tool-Using Language Agents","created":"2026-04-17","cited_by_count":10,"area":"agents"},{"id":"2407.02464","title":"Reliable Confidence Intervals for Information Retrieval Evaluation Using Generative A.I","created":"2024-07-02","cited_by_count":9,"area":null},{"id":"2506.20051","title":"Controlled Retrieval-augmented Context Evaluation for Long-form RAG","created":"2025-06-24","cited_by_count":9,"area":"rag"},{"id":"2609.37647","title":"Evaluating and Benchmarking the System One Model Jev","created":"2026-09-29","cited_by_count":9,"area":null},{"id":"2406.00247","title":"Large Language Models for Relevance Judgment in Product Search","created":"2024-06-01","cited_by_count":8,"area":null},{"id":"2406.14117","title":"An Investigation of Prompt Variations for Zero-shot LLM-based Rankers","created":"2024-06-20","cited_by_count":8,"area":null},{"id":"2503.09902","title":"Conversational Gold: Evaluating Personalized Conversational Search System using Gold Nuggets","created":"2025-03-12","cited_by_count":8,"area":"rag"},{"id":"2401.17645","title":"ReSLLM: Large Language Models are Strong Resource Selectors for Federated Search","created":"2024-01-31","cited_by_count":7,"area":"rag"},{"id":"2404.08137","title":"Generative Information Retrieval Evaluation","created":"2024-04-11","cited_by_count":7,"area":"rag"},{"id":"2404.11960","title":"MCRanker: Generating Diverse Criteria On-the-Fly to Improve Point-wise LLM Rankers","created":"2024-04-18","cited_by_count":7,"area":null},{"id":"2410.03780","title":"Reward-RAG: Enhancing RAG with Reward Driven Supervision","created":"2024-10-03","cited_by_count":7,"area":"rag"},{"id":"2501.19264","title":"mFollowIR: a Multilingual Benchmark for Instruction Following in Retrieval","created":"2025-01-31","cited_by_count":7,"area":null},{"id":"2504.07898","title":"How do Large Language Models Understand Relevance? A Mechanistic Interpretability Perspective","created":"2025-04-10","cited_by_count":7,"area":"mechinterp"},{"id":"2506.10301","title":"Towards Understanding Bias in Synthetic Data for Evaluation","created":"2025-06-12","cited_by_count":7,"area":"synth"},{"id":"2405.11612","title":"Sociotechnical Implications of Generative Artificial Intelligence for Information Access","created":"2024-05-19","cited_by_count":6,"area":null},{"id":"2506.10859","title":"Precise Zero-Shot Pointwise Ranking with LLMs through Post-Aggregated Global Context Information","created":"2025-06-12","cited_by_count":6,"area":null},{"id":"2508.08777","title":"Evaluating Podcast Recommendations with Profile-Aware LLM-as-a-Judge","created":"2025-08-12","cited_by_count":6,"area":null},{"id":"2408.03359","title":"LAMPO: Large Language Models as Preference Machines for Few-shot Ordinal Classification","created":"2024-08-06","cited_by_count":5,"area":null},{"id":"2504.05220","title":"Utility-Focused LLM Annotation for Retrieval and Retrieval-Augmented Generation","created":"2025-04-07","cited_by_count":5,"area":"rag"},{"id":"2504.18748","title":"Generative Product Recommendations for Implicit Superlative Queries","created":"2025-04-26","cited_by_count":5,"area":null},{"id":"2603.18516","title":"Total Recall QA: A Verifiable Evaluation Suite for Deep Research Agents","created":"2026-03-19","cited_by_count":5,"area":"agents"},{"id":"2311.02049","title":"Post Turing: Mapping the landscape of LLM Evaluation","created":"2023-11-03","cited_by_count":4,"area":null},{"id":"2405.00801","title":"\"Ask Me Anything\": How Comcast Uses LLMs to Assist Agents in Real Time","created":"2024-05-01","cited_by_count":4,"area":null},{"id":"2503.23239","title":"Beyond Contrastive Learning: Synthetic Data Enables List-wise Training with Multiple Levels of Relevance","created":"2025-03-29","cited_by_count":4,"area":"synth"},{"id":"2505.04209","title":"To Judge or not to Judge: Using LLM Judgements for Advertiser Keyphrase Relevance at eBay","created":"2025-05-07","cited_by_count":4,"area":null},{"id":"2505.07105","title":"Knowledge Distillation for Enhancing Walmart E-commerce Search Relevance Using Large Language Models","created":"2025-05-11","cited_by_count":4,"area":"distill"},{"id":"2509.03764","title":"LLM-based Relevance Assessment for Web-Scale Search Evaluation at Pinterest","created":"2025-09-03","cited_by_count":4,"area":null},{"id":"2601.15161","title":"Retrieval-Augmented Agentic Rubric Generation for Reliable Medical Response Evaluation","created":"2026-01-21","cited_by_count":4,"area":"rag"},{"id":"2406.14162","title":"DIRAS: Efficient LLM Annotation of Document Relevance in Retrieval Augmented Generation","created":"2024-06-20","cited_by_count":3,"area":"rag"},{"id":"2410.14044","title":"Best in Tau@LLMJudge: Criteria-Based Relevance Evaluation with Llama3","created":"2024-10-17","cited_by_count":3,"area":null},{"id":"2410.21242","title":"Zero-Shot Dense Retrieval with Embeddings from Relevance Feedback","created":"2024-10-28","cited_by_count":3,"area":null},{"id":"2412.12504","title":"Boosting LLM-based Relevance Modeling with Distribution-Aware Robust Learning","created":"2024-12-17","cited_by_count":3,"area":null},{"id":"2505.15856","title":"DisastIR: A Comprehensive Information Retrieval Benchmark for Disaster Management","created":"2025-05-20","cited_by_count":3,"area":null},{"id":"2409.17642","title":"AI Delegates with a Dual Focus: Ensuring Privacy and Strategic Self-Disclosure","created":"2024-09-26","cited_by_count":2,"area":null},{"id":"2411.15396","title":"The Decoy Dilemma in Online Medical Information Evaluation: A Comparative Study of Credibility Assessments by LLM and Human Judges","created":"2024-11-23","cited_by_count":2,"area":null},{"id":"2503.08379","title":"JurisTCU: A Brazilian Portuguese Information Retrieval Dataset with Query Relevance Judgments","created":"2025-03-11","cited_by_count":2,"area":null},{"id":"2504.09816","title":"Augmented Relevance Datasets with Fine-Tuned Small LLMs","created":"2025-04-14","cited_by_count":2,"area":null},{"id":"2504.15689","title":"The Viability of Crowdsourcing for RAG Evaluation","created":"2025-04-22","cited_by_count":2,"area":"rag"},{"id":"2506.07296","title":"HotelMatch-LLM: Joint Multi-Task Training of Small and Large Language Models for Efficient Multimodal Hotel Retrieval","created":"2025-06-08","cited_by_count":2,"area":null},{"id":"2506.17782","title":"Expanding Relevance Judgments for Medical Case-based Retrieval Task with Multimodal LLMs","created":"2025-06-21","cited_by_count":2,"area":"mllm"},{"id":"2508.03628","title":"LLMDistill4Ads: Using Cross-Encoders to Distill from LLM Signals for Advertiser Keyphrase Recommendations at eBay","created":"2025-08-05","cited_by_count":2,"area":null},{"id":"2510.02241","title":"Study on LLMs for Promptagator-Style Dense Retriever Training","created":"2025-10-02","cited_by_count":2,"area":null},{"id":"2512.00390","title":"Mitigating the Threshold Priming Effect in Large Language Model-Based Relevance Judgments via Personality Infusing","created":"2025-11-29","cited_by_count":2,"area":null},{"id":"2512.02555","title":"ADORE: Autonomous Domain-Oriented Relevance Engine for E-commerce","created":"2025-12-02","cited_by_count":2,"area":null},{"id":"2601.08363","title":"PosIR: Position-Aware Heterogeneous Information Retrieval Benchmark","created":"2026-01-13","cited_by_count":2,"area":null},{"id":"2402.11757","title":"Large Language Models for Stemming: Promises, Pitfalls and Failures","created":"2024-02-19","cited_by_count":1,"area":null},{"id":"2410.19974","title":"Evaluating Cost-Accuracy Trade-offs in Multimodal Search Relevance Judgements","created":"2024-10-25","cited_by_count":1,"area":null},{"id":"2411.18968","title":"Perception of Visual Content: Differences Between Humans and Foundation Models","created":"2024-11-28","cited_by_count":1,"area":null},{"id":"2412.11068","title":"RecSys Arena: Pair-wise Recommender System Evaluation with Large Language Models","created":"2024-12-15","cited_by_count":1,"area":null},{"id":"2505.07247","title":"SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models","created":"2025-05-12","cited_by_count":1,"area":null},{"id":"2505.07345","title":"QUPID: Quantified Understanding for Enhanced Performance, Insights, and Decisions in Korean Search Engines","created":"2025-05-12","cited_by_count":1,"area":null},{"id":"2509.01566","title":"CSRM-LLM: Embracing Multilingual LLMs for Cold-Start Relevance Matching in Emerging E-commerce Markets","created":"2025-09-01","cited_by_count":1,"area":null},{"id":"2601.01751","title":"Query-Document Dense Vectors for LLM Relevance Judgment Bias Analysis","created":"2026-01-05","cited_by_count":1,"area":null},{"id":"2601.01862","title":"Judging with Personality and Confidence: A Study on Personality-Conditioned LLM Relevance Assessment","created":"2026-01-05","cited_by_count":1,"area":null},{"id":"2601.09515","title":"SERM: Self-Evolving Relevance Model with Agent-Driven Learning from Massive Query Streams","created":"2026-01-14","cited_by_count":1,"area":null},{"id":"2601.13227","title":"Insider Knowledge: How Much Can RAG Systems Gain from Evaluation Secrets?","created":"2026-01-19","cited_by_count":1,"area":"rag"},{"id":"2602.00052","title":"AI-assisted Protocol Information Extraction For Improved Accuracy and Efficiency in Clinical Trial Workflows","created":"2026-01-19","cited_by_count":1,"area":null},{"id":"2602.06526","title":"Completing Missing Annotation: Multi-Agent Debate for Accurate and Scalable Relevant Assessment for IR Benchmarks","created":"2026-02-06","cited_by_count":1,"area":"agents"},{"id":"2602.23949","title":"HotelQuEST: Balancing Quality and Efficiency in Agentic Search","created":"2026-02-27","cited_by_count":1,"area":"agents"},{"id":"2603.04532","title":"Still Fresh? Evaluating Temporal Drift in Retrieval Benchmarks","created":"2026-03-04","cited_by_count":1,"area":null},{"id":"2604.25683","title":"K-CARE: Knowledge-driven Symmetrical Contextual Anchoring and Analogical Prototype Reasoning for E-commerce Relevance","created":"2026-04-28","cited_by_count":1,"area":"lr"},{"id":"2606.13905","title":"ADORE: Iterative Query Expansion with Retrieval-Grounded Relevance Feedback","created":"2026-06-11","cited_by_count":1,"area":null},{"id":"2606.29894","title":"SABER-Math: Automated Benchmark for Information Retrieval Evaluation in Mathematics","created":"2026-06-29","cited_by_count":1,"area":"agents"},{"id":"2606.30840","title":"Contrastive Reflection for Iterative Prompt Optimization","created":"2026-06-29","cited_by_count":1,"area":"agents"},{"id":"2608.10008","title":"Do LLM Recommenders Know When They're Hallucinating? Auditing Confidence Calibration in Catalog Faithfulness","created":"2026-08-07","cited_by_count":1,"area":null}],"next_cursor":"100"}