{"list":"other","total":51,"rows":[{"id":"1908.10084","title":"Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks","created":"2019-08-27","cited_by_count":9170},{"id":"2001.08361","title":"Scaling Laws for Neural Language Models","created":"2020-01-23","cited_by_count":6586},{"id":"2004.04906","title":"Dense Passage Retrieval for Open-Domain Question Answering","created":"2020-04-10","cited_by_count":3824},{"id":"2009.01325","title":"Learning to summarize from human feedback","created":"2020-09-02","cited_by_count":2588},{"id":"1702.08734","title":"Billion-scale similarity search with GPUs","created":"2017-02-28","cited_by_count":2497},{"id":"2112.09332","title":"WebGPT: Browser-assisted question-answering with human feedback","created":"2021-12-17","cited_by_count":1745},{"id":"2104.08663","title":"BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models","created":"2021-04-17","cited_by_count":1252},{"id":"2112.09118","title":"Unsupervised Dense Information Retrieval with Contrastive Learning","created":"2021-12-16","cited_by_count":1216},{"id":"2210.10760","title":"Scaling Laws for Reward Model Overoptimization","created":"2022-10-19","cited_by_count":1095},{"id":"2407.21787","title":"Large Language Monkeys: Scaling Inference Compute with Repeated Sampling","created":"2024-07-31","cited_by_count":991},{"id":"1603.09320","title":"Efficient and robust approximate nearest neighbor search using Hierarchical Navigable Small World graphs","created":"2016-03-30","cited_by_count":861},{"id":"2007.00808","title":"Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval","created":"2020-07-01","cited_by_count":849},{"id":"1901.04085","title":"Passage Re-ranking with BERT","created":"2019-01-13","cited_by_count":645},{"id":"2004.14974","title":"Fact or Fiction: Verifying Scientific Claims","created":"2020-04-30","cited_by_count":554},{"id":"2404.05961","title":"LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders","created":"2024-04-09","cited_by_count":404},{"id":"2201.03544","title":"The Effects of Reward Misspecification: Mapping and Mitigating Misaligned Models","created":"2022-01-10","cited_by_count":328},{"id":"2310.08319","title":"Fine-Tuning LLaMA for Multi-Stage Text Retrieval","created":"2023-10-12","cited_by_count":272},{"id":"2311.11944","title":"FinanceBench: A New Benchmark for Financial Question Answering","created":"2023-11-20","cited_by_count":270},{"id":"2010.06467","title":"Pretrained Transformers for Text Ranking: BERT and Beyond","created":"2020-10-13","cited_by_count":267},{"id":"2407.19669","title":"mGTE: Generalized Long-Context Text Representation and Reranking Models for Multilingual Text Retrieval","created":"2024-07-29","cited_by_count":236},{"id":"2005.00181","title":"Sparse, Dense, and Attentional Representations for Text Retrieval","created":"2020-05-01","cited_by_count":214},{"id":"1910.14424","title":"Multi-Stage Document Ranking with BERT","created":"2019-10-31","cited_by_count":201},{"id":"1909.00986","title":"Certified Robustness to Adversarial Word Substitutions","created":"2019-09-03","cited_by_count":168},{"id":"1905.01969","title":"Poly-encoders: Transformer Architectures and Pre-training Strategies for Fast and Accurate Multi-sentence Scoring","created":"2019-04-22","cited_by_count":165},{"id":"2407.12883","title":"BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval","created":"2024-07-16","cited_by_count":158},{"id":"2312.02724","title":"RankZephyr: Effective and Robust Zero-Shot Listwise Reranking is a Breeze!","created":"2023-12-05","cited_by_count":155},{"id":"2406.02900","title":"Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms","created":"2024-06-05","cited_by_count":143},{"id":"2210.10634","title":"RankT5: Fine-Tuning T5 for Text Ranking with Ranking Losses","created":"2022-10-12","cited_by_count":115},{"id":"2207.06300","title":"Re2G: Retrieve, Rerank, Generate","created":"2022-07-13","cited_by_count":102},{"id":"2101.08751","title":"Rethink Training of BERT Rerankers in Multi-Stage Retrieval Pipeline","created":"2021-01-21","cited_by_count":65},{"id":"2410.04343","title":"Inference Scaling for Long-Context Retrieval Augmented Generation","created":"2024-10-06","cited_by_count":65},{"id":"1804.05936","title":"Learning a Deep Listwise Context Model for Ranking Refinement","created":"2018-04-16","cited_by_count":62},{"id":"2404.12096","title":"LongEmbed: Extending Embedding Models for Long Context Retrieval","created":"2024-04-18","cited_by_count":48},{"id":"2311.00168","title":"The Alignment Ceiling: Objective Mismatch in Reinforcement Learning from Human Feedback","created":"2023-10-31","cited_by_count":42},{"id":"2410.05318","title":"Improving LLM Reasoning through Scaling Inference Computation with Collaborative Verification","created":"2024-10-05","cited_by_count":40},{"id":"2406.16828","title":"Ragnar\\\"ok: A Reusable RAG Framework and Baselines for TREC 2024 Retrieval-Augmented Generation Track","created":"2024-06-24","cited_by_count":32},{"id":"2403.18684","title":"Scaling Laws For Dense Retrieval","created":"2024-03-27","cited_by_count":29},{"id":"2405.00175","title":"Towards a Search Engine for Machines: Unified Ranking for Multiple Retrieval-Augmented Large Language Models","created":"2024-04-30","cited_by_count":23},{"id":"1811.04415","title":"Learning Groupwise Multivariate Scoring Functions Using Deep Neural Networks","created":"2018-11-11","cited_by_count":22},{"id":"2002.01854","title":"Interpretable & Time-Budget-Constrained Contextualization for Re-Ranking","created":"2020-02-04","cited_by_count":21},{"id":"2212.06121","title":"In Defense of Cross-Encoders for Zero-Shot Retrieval","created":"2022-12-12","cited_by_count":21},{"id":"2203.10053","title":"RELIC: Retrieving Evidence for Literary Claims","created":"2022-03-18","cited_by_count":18},{"id":"2402.14151","title":"BIRCO: A Benchmark of Information Retrieval Tasks with Complex Objectives","created":"2024-02-21","cited_by_count":15},{"id":"2405.14589","title":"Top-Down Partitioning for Efficient List-Wise Ranking","created":"2024-05-23","cited_by_count":13},{"id":"2311.09175","title":"Can Query Expansion Improve Generalization of Strong Cross-Encoder Rankers?","created":"2023-11-15","cited_by_count":12},{"id":"2004.13012","title":"Choppy: Cut Transformer For Ranked List Truncation","created":"2020-04-26","cited_by_count":11},{"id":"1811.09300","title":"Strength in Numbers: Trading-off Robustness and Computation via Adversarially-Trained Ensembles","created":"2018-11-22","cited_by_count":8},{"id":"2103.03335","title":"A Systematic Evaluation of Transfer Learning and Pseudo-labeling with BERT-based Ranking Models","created":"2021-03-04","cited_by_count":8},{"id":"2310.04407","title":"Policy-Gradient Training of Language Models for Ranking","created":"2023-10-06","cited_by_count":5},{"id":"2403.16435","title":"InstUPR : Instruction-based Unsupervised Passage Reranking with Large Language Models","created":"2024-03-25","cited_by_count":3},{"id":"2405.01122","title":"Generative Relevance Feedback and Convergence of Adaptive Re-Ranking: University of Glasgow Terrier Team at TREC DL 2023","created":"2024-05-02","cited_by_count":1}],"next_cursor":null}