{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/re-ranking/papers/5","list_of":"/task/re-ranking","task":"Re-Ranking","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":5,"pages_in_order":8,"rows_per_page":100,"rows":[401,500],"of":743,"counts":{"archive_papers_tagged":743,"with_a_code_link":300,"where_syntology_ran_a_sample":71,"not_listed_spam_title":0,"listed":743,"listed_where_code_ran":71,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":59,"every_run_a_failure_of_syntologys_instrument":12,"listed_with_a_run_with_no_instrument_failure":59,"listed_every_run_a_failure_of_syntologys_instrument":12,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/re-ranking","prev":"/task/re-ranking/papers/4","next":"/task/re-ranking/papers/6","papers":[{"url":null,"slug":"content-based-image-retrieval-for-multi-class","title":"Content-Based Image Retrieval for Multi-Class Volumetric Radiology Images: A Benchmark Study","date":"2024-05-15","arxiv_id":"2405.09334","repositories_listed":0,"syntology":null},{"url":null,"slug":"full-stage-learning-to-rank-a-unified","title":"Full Stage Learning to Rank: A Unified Framework for Multi-Stage Systems","date":"2024-05-08","arxiv_id":"2405.04844","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-reproducibility-study-of-plaid","title":"A Reproducibility Study of PLAID","date":"2024-04-23","arxiv_id":"2404.14989","repositories_listed":0,"syntology":null},{"url":null,"slug":"splate-sparse-late-interaction-retrieval","title":"SPLATE: Sparse Late Interaction Retrieval","date":"2024-04-22","arxiv_id":"2404.13950","repositories_listed":0,"syntology":null},{"url":null,"slug":"is-table-retrieval-a-solved-problem-join","title":"Is Table Retrieval a Solved Problem? Exploring Join-Aware Multi-Table Retrieval","date":"2024-04-15","arxiv_id":"2404.09889","repositories_listed":0,"syntology":null},{"url":null,"slug":"clinlinker-medical-entity-linking-of-clinical","title":"ClinLinker: Medical Entity Linking of Clinical Concept Mentions in Spanish","date":"2024-04-09","arxiv_id":"2404.06367","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-legal-document-retrieval-a-multi","title":"Enhancing Legal Document Retrieval: A Multi-Phase Approach with Large Language Models","date":"2024-03-26","arxiv_id":"2403.18093","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-retrieval-for-rag-based-question","title":"Improving Retrieval for RAG based Question Answering Models on Financial Documents","date":"2024-03-23","arxiv_id":"2404.07221","repositories_listed":0,"syntology":null},{"url":null,"slug":"selecting-query-bag-as-pseudo-relevance","title":"Selecting Query-bag as Pseudo Relevance Feedback for Information-seeking Conversations","date":"2024-03-22","arxiv_id":"2404.04272","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-thorough-comparison-of-cross-encoders-and","title":"A Thorough Comparison of Cross-Encoders and LLMs for Reranking SPLADE","date":"2024-03-15","arxiv_id":"2403.10407","repositories_listed":0,"syntology":null},{"url":null,"slug":"bifurcated-attention-for-single-context-large","title":"Bifurcated Attention: Accelerating Massively Parallel Decoding with Shared Prefixes in LLMs","date":"2024-03-13","arxiv_id":"2403.08845","repositories_listed":0,"syntology":null},{"url":null,"slug":"recost-external-knowledge-guided-data","title":"RECOST: External Knowledge Guided Data-efficient Instruction Tuning","date":"2024-02-27","arxiv_id":"2402.17355","repositories_listed":0,"syntology":null},{"url":null,"slug":"text2pic-swift-enhancing-long-text-to-image","title":"CFIR: Fast and Effective Long-Text To Image Retrieval for Large Corpora","date":"2024-02-23","arxiv_id":"2402.15276","repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-translation-for-optimal-recall","title":"Leveraging Translation For Optimal Recall: Tailoring LLM Personalization With User Profiles","date":"2024-02-21","arxiv_id":"2402.13500","repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-opposite-gender-interaction-ratio","title":"Leveraging Opposite Gender Interaction Ratio as a Path towards Fairness in Online Dating Recommendations Based on User Sexual Orientation","date":"2024-02-19","arxiv_id":"2402.12541","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-systematic-review-of-data-to-text-nlg","title":"A Systematic Review of Data-to-Text NLG","date":"2024-02-13","arxiv_id":"2402.08496","repositories_listed":0,"syntology":null},{"url":null,"slug":"constrained-multiview-representation-for-self","title":"Constrained Multiview Representation for Self-supervised Contrastive Learning","date":"2024-02-05","arxiv_id":"2402.03456","repositories_listed":0,"syntology":null},{"url":null,"slug":"regressing-transformers-for-data-efficient","title":"Regressing Transformers for Data-efficient Visual Place Recognition","date":"2024-01-29","arxiv_id":"2401.16304","repositories_listed":0,"syntology":null},{"url":null,"slug":"query-exposure-prediction-for-groups-of","title":"Query Exposure Prediction for Groups of Documents in Rankings","date":"2024-01-24","arxiv_id":"2401.13434","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-recommendation-diversity-by-re","title":"Enhancing Recommendation Diversity by Re-ranking with Large Language Models","date":"2024-01-21","arxiv_id":"2401.11506","repositories_listed":0,"syntology":null},{"url":null,"slug":"revealing-the-hidden-impact-of-top-n-metrics","title":"Revealing the Hidden Impact of Top-N Metrics on Optimization in Recommender Systems","date":"2024-01-16","arxiv_id":"2401.08444","repositories_listed":0,"syntology":null},{"url":null,"slug":"multislot-reranker-a-generic-model-based-re","title":"MultiSlot ReRanker: A Generic Model-based Re-Ranking Framework in Recommendation Systems","date":"2024-01-11","arxiv_id":"2401.06293","repositories_listed":0,"syntology":null},{"url":null,"slug":"guitar-gradient-pruning-toward-fast-neural","title":"GUITAR: Gradient Pruning toward Fast Neural Ranking","date":"2023-12-28","arxiv_id":"2312.16828","repositories_listed":0,"syntology":null},{"url":null,"slug":"training-free-zero-shot-composed-image","title":"Training-free Zero-shot Composed Image Retrieval with Local Concept Reranking","date":"2023-12-14","arxiv_id":"2312.08924","repositories_listed":0,"syntology":null},{"url":null,"slug":"relevance-feedback-strategies-for-recall","title":"Relevance feedback strategies for recall-oriented neural information retrieval","date":"2023-11-25","arxiv_id":"2311.15110","repositories_listed":0,"syntology":null},{"url":null,"slug":"dialogizer-context-aware-conversational-qa","title":"Dialogizer: Context-aware Conversational-QA Dataset Generation from Textual Sources","date":"2023-11-09","arxiv_id":"2311.07589","repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-neural-ranking-using-forward","title":"Efficient Neural Ranking using Forward Indexes and Lightweight Encoders","date":"2023-11-02","arxiv_id":"2311.01263","repositories_listed":0,"syntology":null},{"url":null,"slug":"gar-meets-rag-paradigm-for-zero-shot","title":"GAR-meets-RAG Paradigm for Zero-Shot Information Retrieval","date":"2023-10-31","arxiv_id":"2310.20158","repositories_listed":0,"syntology":null},{"url":null,"slug":"parade-passage-ranking-using-demonstrations","title":"PaRaDe: Passage Ranking using Demonstrations with Large Language Models","date":"2023-10-22","arxiv_id":"2310.14408","repositories_listed":0,"syntology":null},{"url":null,"slug":"contextual-data-augmentation-for-task","title":"Contextual Data Augmentation for Task-Oriented Dialog Systems","date":"2023-10-16","arxiv_id":"2310.10380","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-large-language-model-fine-tuning","title":"Improving Large Language Model Fine-tuning for Solving Math Problems","date":"2023-10-16","arxiv_id":"2310.10047","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-completely-locale-independent-session-based","title":"A Completely Locale-independent Session-based Recommender System by Leveraging Trained Model","date":"2023-10-11","arxiv_id":"2310.07281","repositories_listed":0,"syntology":null},{"url":null,"slug":"answer-candidate-type-selection-text-to-text","title":"Answer Candidate Type Selection: Text-to-Text Language Model for Closed Book Question Answering Meets Knowledge Graphs","date":"2023-10-10","arxiv_id":"2310.07008","repositories_listed":0,"syntology":null},{"url":null,"slug":"tpdr-a-novel-two-step-transformer-based","title":"TPDR: A Novel Two-Step Transformer-based Product and Class Description Match and Retrieval Method","date":"2023-10-05","arxiv_id":"2310.03491","repositories_listed":0,"syntology":null},{"url":null,"slug":"large-language-models-meet-knowledge-graphs","title":"Large Language Models Meet Knowledge Graphs to Answer Factoid Questions","date":"2023-10-03","arxiv_id":"2310.02166","repositories_listed":0,"syntology":null},{"url":null,"slug":"fairness-for-all-investigating-harms-to","title":"Fairness for All: Investigating Harms to Within-Group Individuals in Producer Fairness Re-ranking Optimization -- A Reproducibility Study","date":"2023-09-17","arxiv_id":"2309.09277","repositories_listed":0,"syntology":null},{"url":null,"slug":"uncertainty-aware-multi-view-visual-semantic","title":"Dynamic Visual Semantic Sub-Embeddings and Fast Re-Ranking","date":"2023-09-15","arxiv_id":"2309.08154","repositories_listed":0,"syntology":null},{"url":null,"slug":"large-language-models-for-generative","title":"Large Language Models for Generative Recommendation: A Survey and Visionary Discussions","date":"2023-09-03","arxiv_id":"2309.01157","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-multi-perspective-learning-to-rank-approach","title":"A Multi-Perspective Learning to Rank Approach to Support Children's Information Seeking in the Classroom","date":"2023-08-29","arxiv_id":"2308.15265","repositories_listed":0,"syntology":null},{"url":null,"slug":"ensuring-user-side-fairness-in-dynamic","title":"Ensuring User-side Fairness in Dynamic Recommender Systems","date":"2023-08-29","arxiv_id":"2308.15651","repositories_listed":0,"syntology":null},{"url":null,"slug":"finding-already-debunked-narratives-via","title":"Breaking Language Barriers with MMTweets: Advancing Cross-Lingual Debunked Narrative Retrieval for Fact-Checking","date":"2023-08-10","arxiv_id":"2308.05680","repositories_listed":0,"syntology":null},{"url":null,"slug":"mobile-supply-the-last-piece-of-jigsaw-of","title":"Mobile Supply: The Last Piece of Jigsaw of Recommender System","date":"2023-08-07","arxiv_id":"2308.03855","repositories_listed":0,"syntology":null},{"url":null,"slug":"large-scale-fully-unsupervised-re","title":"Large-scale Fully-Unsupervised Re-Identification","date":"2023-07-26","arxiv_id":"2307.14278","repositories_listed":0,"syntology":null},{"url":null,"slug":"large-language-models-as-batteries-included","title":"Large Language Models as Batteries-Included Zero-Shot ESCO Skills Matchers","date":"2023-07-07","arxiv_id":"2307.03539","repositories_listed":0,"syntology":null},{"url":null,"slug":"effective-matching-of-patients-to-clinical","title":"Effective Matching of Patients to Clinical Trials using Entity Extraction and Neural Re-ranking","date":"2023-07-01","arxiv_id":"2307.00381","repositories_listed":0,"syntology":null},{"url":null,"slug":"re-rank-expand-repeat-adaptive-query","title":"Adaptive Latent Entity Expansion for Document Retrieval","date":"2023-06-29","arxiv_id":"2306.17082","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-documents-with-multidimensional","title":"Enhancing Documents with Multidimensional Relevance Statements in Cross-encoder Re-ranking","date":"2023-06-19","arxiv_id":"2306.10979","repositories_listed":0,"syntology":null},{"url":null,"slug":"online-distillation-for-pseudo-relevance","title":"Online Distillation for Pseudo-Relevance Feedback","date":"2023-06-16","arxiv_id":"2306.09657","repositories_listed":0,"syntology":null},{"url":null,"slug":"distillation-strategies-for-discriminative","title":"Distillation Strategies for Discriminative Speech Recognition Rescoring","date":"2023-06-15","arxiv_id":"2306.09452","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-fairness-in-personalized-ads-using","title":"Towards Fairness in Personalized Ads Using Impression Variance Aware Reinforcement Learning","date":"2023-06-05","arxiv_id":"2306.03293","repositories_listed":0,"syntology":null},{"url":null,"slug":"beir-pl-zero-shot-information-retrieval","title":"BEIR-PL: Zero Shot Information Retrieval Benchmark for the Polish Language","date":"2023-05-31","arxiv_id":"2305.19840","repositories_listed":0,"syntology":null},{"url":null,"slug":"trer-a-lightweight-transformer-re-ranking","title":"TReR: A Lightweight Transformer Re-Ranking Approach for 3D LiDAR Place Recognition","date":"2023-05-29","arxiv_id":"2305.18013","repositories_listed":0,"syntology":null},{"url":null,"slug":"graph-meets-llm-a-novel-approach-to","title":"Graph Meets LLM: A Novel Approach to Collaborative Filtering for Robust Conversational Understanding","date":"2023-05-23","arxiv_id":"2305.14449","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-factor-sequential-re-ranking-with","title":"Multi-factor Sequential Re-ranking with Perception-Aware Diversification","date":"2023-05-21","arxiv_id":"2305.12420","repositories_listed":0,"syntology":null},{"url":null,"slug":"evaluating-embedding-apis-for-information","title":"Evaluating Embedding APIs for Information Retrieval","date":"2023-05-10","arxiv_id":"2305.06300","repositories_listed":0,"syntology":null},{"url":null,"slug":"empowering-language-model-with-guided","title":"Empowering Language Model with Guided Knowledge Fusion for Biomedical Document Re-ranking","date":"2023-05-07","arxiv_id":"2305.04344","repositories_listed":0,"syntology":null},{"url":null,"slug":"pay-more-attention-to-relation-exploration","title":"Pay More Attention to Relation Exploration for Knowledge Base Question Answering","date":"2023-05-03","arxiv_id":"2305.02118","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-to-re-rank-with-constrained-meta","title":"Learning to Re-rank with Constrained Meta-Optimal Transport","date":"2023-04-29","arxiv_id":"2305.00319","repositories_listed":0,"syntology":null},{"url":null,"slug":"person-re-id-through-unsupervised-hypergraph","title":"Person Re-ID through Unsupervised Hypergraph Rank Selection and Fusion","date":"2023-04-27","arxiv_id":"2304.14321","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploiting-simulated-user-feedback-for","title":"Exploiting Simulated User Feedback for Conversational Search: Ranking, Rewriting, and Beyond","date":"2023-04-26","arxiv_id":"2304.13874","repositories_listed":0,"syntology":null},{"url":null,"slug":"dialogue-contextualized-re-ranking-for","title":"Dialogue-Contextualized Re-ranking for Medical History-Taking","date":"2023-04-04","arxiv_id":"2304.01974","repositories_listed":0,"syntology":null},{"url":null,"slug":"if-at-first-you-don-t-succeed-test-time-re","title":"If At First You Don't Succeed: Test Time Re-ranking for Zero-shot, Cross-domain Retrieval","date":"2023-03-30","arxiv_id":"2303.17703","repositories_listed":0,"syntology":null},{"url":null,"slug":"globalner-incorporating-non-local-information","title":"GlobalNER: Incorporating Non-local Information into Named Entity Recognition","date":"2023-03-06","arxiv_id":"2303.02915","repositories_listed":0,"syntology":null},{"url":null,"slug":"kg-eco-knowledge-graph-enhanced-entity","title":"KG-ECO: Knowledge Graph Enhanced Entity Correction for Query Rewriting","date":"2023-02-21","arxiv_id":"2302.10454","repositories_listed":0,"syntology":null},{"url":null,"slug":"actional-atomic-concept-learning-for","title":"Actional Atomic-Concept Learning for Demystifying Vision-Language Navigation","date":"2023-02-13","arxiv_id":"2302.06072","repositories_listed":0,"syntology":null},{"url":null,"slug":"relatedly-scaffolding-literature-reviews-with","title":"Relatedly: Scaffolding Literature Reviews with Existing Related Work Sections","date":"2023-02-13","arxiv_id":"2302.06754","repositories_listed":0,"syntology":null},{"url":null,"slug":"lexical-simplification-using-multi-level-and","title":"Lexical Simplification using multi level and modular approach","date":"2023-02-03","arxiv_id":"2302.01823","repositories_listed":0,"syntology":null},{"url":null,"slug":"using-in-context-learning-to-improve-dialogue","title":"Using In-Context Learning to Improve Dialogue Safety","date":"2023-02-02","arxiv_id":"2302.00871","repositories_listed":0,"syntology":null},{"url":null,"slug":"embeddistill-a-geometric-knowledge","title":"EmbedDistill: A Geometric Knowledge Distillation for Information Retrieval","date":"2023-01-27","arxiv_id":"2301.12005","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-noise-robustness-for-spoken-content","title":"Improving Noise Robustness for Spoken Content Retrieval using Semi-supervised ASR and N-best Transcripts for BERT-based Ranking Models","date":"2023-01-15","arxiv_id":"2301.06056","repositories_listed":0,"syntology":null},{"url":null,"slug":"inpars-light-cost-effective-unsupervised","title":"InPars-Light: Cost-Effective Unsupervised Training of Efficient Rankers","date":"2023-01-08","arxiv_id":"2301.02998","repositories_listed":0,"syntology":null},{"url":null,"slug":"improved-beam-search-for-hallucination","title":"Improved Beam Search for Hallucination Mitigation in Abstractive Summarization","date":"2022-12-06","arxiv_id":"2212.02712","repositories_listed":0,"syntology":null},{"url":null,"slug":"structvpr-distill-structural-knowledge-with","title":"StructVPR: Distill Structural Knowledge with Weighting Samples for Visual Place Recognition","date":"2022-12-02","arxiv_id":"2212.00937","repositories_listed":0,"syntology":null},{"url":null,"slug":"diverse-multi-answer-retrieval-with-1","title":"Diverse Multi-Answer Retrieval with Determinantal Point Processes","date":"2022-11-29","arxiv_id":"2211.16029","repositories_listed":0,"syntology":null},{"url":null,"slug":"noisy-channel-for-automatic-text","title":"Noisy Channel for Automatic Text Simplification","date":"2022-11-06","arxiv_id":"2211.03152","repositories_listed":0,"syntology":null},{"url":"/paper/metric-guided-distillation-distilling","slug":"metric-guided-distillation-distilling","title":"Metric-guided Distillation: Distilling Knowledge from the Metric to Ranker and Retriever for Generative Commonsense Reasoning","date":"2022-10-21","arxiv_id":"2210.11708","repositories_listed":0,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/metric-guided-distillation-distilling#ran","syntology_url":"https://syntology.ai/paper/2210.11708","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2210.11708"}},"official":null}},{"url":null,"slug":"retrieval-augmentation-for-t5-re-ranker-using","title":"Retrieval Augmentation for T5 Re-ranker using External Sources","date":"2022-10-11","arxiv_id":"2210.05145","repositories_listed":0,"syntology":null},{"url":null,"slug":"specialized-re-ranking-a-novel-retrieval","title":"Specialized Re-Ranking: A Novel Retrieval-Verification Framework for Cloth Changing Person Re-Identification","date":"2022-10-07","arxiv_id":"2210.03592","repositories_listed":0,"syntology":null},{"url":null,"slug":"textgraphs-16-natural-language-premise","title":"TextGraphs-16 Natural Language Premise Selection Task: Zero-Shot Premise Selection with Prompting Generative Language Models","date":"2022-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"fid-light-efficient-and-effective-retrieval","title":"FiD-Light: Efficient and Effective Retrieval-Augmented Text Generation","date":"2022-09-28","arxiv_id":"2209.14290","repositories_listed":0,"syntology":null},{"url":null,"slug":"t5ql-taming-language-models-for-sql","title":"T5QL: Taming language models for SQL generation","date":"2022-09-21","arxiv_id":"2209.10254","repositories_listed":0,"syntology":null},{"url":null,"slug":"multilingual-transformer-language-model-for","title":"Multilingual Transformer Language Model for Speech Recognition in Low-resource Languages","date":"2022-09-08","arxiv_id":"2209.04041","repositories_listed":0,"syntology":null},{"url":null,"slug":"raguel-recourse-aware-group-unfairness","title":"RAGUEL: Recourse-Aware Group Unfairness Elimination","date":"2022-08-30","arxiv_id":"2208.14175","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-confidence-aware-calibrated","title":"Towards Confidence-aware Calibrated Recommendation","date":"2022-08-22","arxiv_id":"2208.10192","repositories_listed":0,"syntology":null},{"url":null,"slug":"scattered-or-connected-an-optimized-parameter","title":"Scattered or Connected? An Optimized Parameter-efficient Tuning Approach for Information Retrieval","date":"2022-08-21","arxiv_id":"2208.09847","repositories_listed":0,"syntology":null},{"url":null,"slug":"real-time-short-video-recommendation-on","title":"Real-time Short Video Recommendation on Mobile Devices","date":"2022-08-20","arxiv_id":"2208.09577","repositories_listed":0,"syntology":null},{"url":null,"slug":"unimib-at-trec-2021-clinical-trials-track","title":"UNIMIB at TREC 2021 Clinical Trials Track","date":"2022-07-27","arxiv_id":"2207.13514","repositories_listed":0,"syntology":null},{"url":null,"slug":"contrastive-information-transfer-for-pre","title":"Contrastive Information Transfer for Pre-Ranking Systems","date":"2022-07-07","arxiv_id":"2207.03073","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-role-of-complex-nlp-in-transformers-for","title":"The Role of Complex NLP in Transformers for Text Ranking?","date":"2022-07-06","arxiv_id":"2207.02522","repositories_listed":0,"syntology":null},{"url":null,"slug":"accurate-instance-level-cad-model-retrieval","title":"Accurate Instance-Level CAD Model Retrieval in a Large-Scale Database","date":"2022-07-04","arxiv_id":"2207.01339","repositories_listed":0,"syntology":null},{"url":null,"slug":"simprov-scalable-image-provenance-framework","title":"SImProv: Scalable Image Provenance Framework for Robust Content Attribution","date":"2022-06-28","arxiv_id":"2206.14245","repositories_listed":0,"syntology":null},{"url":null,"slug":"research-a-pre-computing-solution-for-online","title":"PCDF: A Parallel-Computing Distributed Framework for Sponsored Search Advertising Serving","date":"2022-06-26","arxiv_id":"2206.12893","repositories_listed":0,"syntology":null},{"url":null,"slug":"feature-aware-diversified-re-ranking-with","title":"Feature-aware Diversified Re-ranking with Disentangled Representations for Relevant Recommendation","date":"2022-06-10","arxiv_id":"2206.05020","repositories_listed":0,"syntology":null},{"url":null,"slug":"few-shot-question-generation-for-personalized","title":"Few-shot Question Generation for Personalized Feedback in Intelligent Tutoring Systems","date":"2022-06-08","arxiv_id":"2206.04187","repositories_listed":0,"syntology":null},{"url":null,"slug":"leibi-coliee-2022-aggregating-tuned-lexical","title":"LeiBi@COLIEE 2022: Aggregating Tuned Lexical Models with a Cluster-driven BERT-based Model for Case Law Retrieval","date":"2022-05-26","arxiv_id":"2205.13351","repositories_listed":0,"syntology":null},{"url":null,"slug":"what-makes-data-to-text-generation-hard-for","title":"What Makes Data-to-Text Generation Hard for Pretrained Language Models?","date":"2022-05-23","arxiv_id":"2205.11505","repositories_listed":0,"syntology":null},{"url":null,"slug":"autofas-automatic-feature-and-architecture","title":"AutoFAS: Automatic Feature and Architecture Selection for Pre-Ranking System","date":"2022-05-19","arxiv_id":"2205.09394","repositories_listed":0,"syntology":null},{"url":null,"slug":"controlling-formality-in-low-resource-nmt","title":"Controlling Formality in Low-Resource NMT with Domain Adaptation and Re-Ranking: SLT-CDT-UoS at IWSLT2022","date":"2022-05-12","arxiv_id":"2205.05990","repositories_listed":0,"syntology":null},{"url":null,"slug":"subverting-fair-image-search-with-generative","title":"Subverting Fair Image Search with Generative Adversarial Perturbations","date":"2022-05-05","arxiv_id":"2205.02414","repositories_listed":0,"syntology":null},{"url":null,"slug":"document-retrieval-and-claim-verification-to","title":"Document Retrieval and Claim Verification to Mitigate COVID-19 Misinformation","date":"2022-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null}],"record_sha256":"5e3c00414faf75e3ad53898b04c18215e1f41ab233b3e7fa4d284bde433739fd","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}