{"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/retrieval/papers/102","list_of":"/task/retrieval","task":"Retrieval","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":102,"pages_in_order":143,"rows_per_page":100,"rows":[10101,10200],"of":14297,"counts":{"archive_papers_tagged":14297,"with_a_code_link":5274,"where_syntology_ran_a_sample":1303,"not_listed_spam_title":0,"listed":14297,"listed_where_code_ran":1303,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":1067,"every_run_a_failure_of_syntologys_instrument":236,"listed_with_a_run_with_no_instrument_failure":1067,"listed_every_run_a_failure_of_syntologys_instrument":236,"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/retrieval","prev":"/task/retrieval/papers/101","next":"/task/retrieval/papers/103","papers":[{"url":null,"slug":"dsc-iitism-at-fincausal-2021-combining-pos","title":"DSC-IITISM at FinCausal 2021: Combining POS tagging with Attention-based Contextual Representations for Identifying Causal Relationships in Financial Documents","date":"2021-10-31","arxiv_id":"2111.00490","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-spatio-temporal-identity-verification","title":"whu-nercms at trecvid2021:instance search task","date":"2021-10-30","arxiv_id":"2111.00228","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-keyphrase-completion","title":"Deep Keyphrase Completion","date":"2021-10-29","arxiv_id":"2111.01910","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-representations-for-zero-shot","title":"Learning Representations for Zero-Shot Retrieval over Structured Data","date":"2021-10-29","arxiv_id":"2111.00123","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-tractable-mathematical-reasoning","title":"Towards Tractable Mathematical Reasoning: Challenges, Strategies, and Opportunities for Solving Math Word Problems","date":"2021-10-29","arxiv_id":"2111.05364","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-ai-based-approach-for-tracing-content","title":"Tracing Content Requirements in Financial Documents using Multi-granularity Text Analysis","date":"2021-10-28","arxiv_id":"2110.14960","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-stage-clarification-in-conversational","title":"Multi-stage Clarification in Conversational AI: The case of Question-Answering Dialogue Systems","date":"2021-10-28","arxiv_id":"2110.15235","repositories_listed":0,"syntology":null},{"url":null,"slug":"cbir-using-pre-trained-neural-networks","title":"CBIR using Pre-Trained Neural Networks","date":"2021-10-27","arxiv_id":"2110.14455","repositories_listed":0,"syntology":null},{"url":null,"slug":"don-t-read-just-look-main-content-extraction","title":"Don't read, just look: Main content extraction from web pages using visual features","date":"2021-10-27","arxiv_id":"2110.14164","repositories_listed":0,"syntology":null},{"url":null,"slug":"domain-adaptation-in-multi-view-embedding-for","title":"Domain Adaptation in Multi-View Embedding for Cross-Modal Video Retrieval","date":"2021-10-25","arxiv_id":"2110.12812","repositories_listed":0,"syntology":null},{"url":null,"slug":"where-were-my-keys-aggregating-spatial","title":"Where were my keys? -- Aggregating Spatial-Temporal Instances of Objects for Efficient Retrieval over Long Periods of Time","date":"2021-10-25","arxiv_id":"2110.13061","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-asymmetric-hashing-with-dual-semantic","title":"Deep Asymmetric Hashing with Dual Semantic Regression and Class Structure Quantization","date":"2021-10-24","arxiv_id":"2110.12478","repositories_listed":0,"syntology":null},{"url":null,"slug":"mic-model-agnostic-integrated-cross-channel","title":"MIC: Model-agnostic Integrated Cross-channel Recommenders","date":"2021-10-22","arxiv_id":"2110.11570","repositories_listed":0,"syntology":null},{"url":null,"slug":"wacky-weights-in-learned-sparse","title":"Wacky Weights in Learned Sparse Representations and the Revenge of Score-at-a-Time Query Evaluation","date":"2021-10-22","arxiv_id":"2110.11540","repositories_listed":0,"syntology":null},{"url":null,"slug":"contrastive-document-representation-learning","title":"Contrastive Document Representation Learning with Graph Attention Networks","date":"2021-10-20","arxiv_id":"2110.10778","repositories_listed":0,"syntology":null},{"url":null,"slug":"privacy-in-open-search-a-review-of-challenges","title":"Privacy in Open Search: A Review of Challenges and Solutions","date":"2021-10-20","arxiv_id":"2110.10720","repositories_listed":0,"syntology":null},{"url":null,"slug":"vldeformer-learning-visual-semantic","title":"VLDeformer: Vision-Language Decomposed Transformer for Fast Cross-Modal Retrieval","date":"2021-10-20","arxiv_id":"2110.11338","repositories_listed":0,"syntology":null},{"url":null,"slug":"contrastive-learning-of-visual-semantic","title":"Contrastive Learning of Visual-Semantic Embeddings","date":"2021-10-17","arxiv_id":"2110.08872","repositories_listed":0,"syntology":null},{"url":null,"slug":"deconfounded-and-explainable-interactive","title":"Deconfounded and Explainable Interactive Vision-Language Retrieval of Complex Scenes","date":"2021-10-17","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"low-precision-quantization-for-efficient","title":"Low-Precision Quantization for Efficient Nearest Neighbor Search","date":"2021-10-17","arxiv_id":"2110.08919","repositories_listed":0,"syntology":null},{"url":null,"slug":"challenges-in-generalization-in-open-domain-1","title":"Challenges in Generalization in Open Domain Question Answering","date":"2021-10-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-knowledge-in-multilingual","title":"Leveraging Knowledge in Multilingual Commonsense Reasoning","date":"2021-10-16","arxiv_id":"2110.08462","repositories_listed":0,"syntology":null},{"url":null,"slug":"multimodal-dialogue-response-generation","title":"Multimodal Dialogue Response Generation","date":"2021-10-16","arxiv_id":"2110.08515","repositories_listed":0,"syntology":null},{"url":null,"slug":"multimodal-entity-tagging-with-multimodal","title":"Multimodal Entity Tagging with Multimodal Knowledge Base","date":"2021-10-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"noise-augmented-privacy-preserving-empirical","title":"Noise-Augmented Privacy-Preserving Empirical Risk Minimization with Dual-purpose Regularizer and Privacy Budget Retrieval and Recycling","date":"2021-10-16","arxiv_id":"2110.08676","repositories_listed":0,"syntology":null},{"url":null,"slug":"pdmm-a-novel-primal-dual-majorization","title":"PDMM: A novel Primal-Dual Majorization-Minimization algorithm for Poisson Phase-Retrieval problem","date":"2021-10-16","arxiv_id":"2110.08600","repositories_listed":0,"syntology":null},{"url":null,"slug":"semantic-search-as-extractive-paraphrase-span","title":"Semantic Search as Extractive Paraphrase Span Detection","date":"2021-10-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"spe-symmetrical-prompt-enhancement-for","title":"SPE: Symmetrical Prompt Enhancement for Factual Knowledge Retrieval","date":"2021-10-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"cascaded-fast-and-slow-models-for-efficient-1","title":"Cascaded Fast and Slow Models for Efficient Semantic Code Search","date":"2021-10-15","arxiv_id":"2110.07811","repositories_listed":0,"syntology":null},{"url":null,"slug":"spot-better-frozen-model-adaptation-through","title":"SPoT: Better Frozen Model Adaptation through Soft Prompt Transfer","date":"2021-10-15","arxiv_id":"2110.07904","repositories_listed":0,"syntology":null},{"url":null,"slug":"coarse-to-fine-video-retrieval-before-moment","title":"Coarse to Fine: Video Retrieval before Moment Localization","date":"2021-10-14","arxiv_id":"2110.07201","repositories_listed":0,"syntology":null},{"url":null,"slug":"creating-user-interface-mock-ups-from-high","title":"Creating User Interface Mock-ups from High-Level Text Descriptions with Deep-Learning Models","date":"2021-10-14","arxiv_id":"2110.07775","repositories_listed":0,"syntology":null},{"url":null,"slug":"cross-lingual-genqa-a-language-agnostic","title":"Cross-Lingual Open-Domain Question Answering with Answer Sentence Generation","date":"2021-10-14","arxiv_id":"2110.07150","repositories_listed":0,"syntology":null},{"url":null,"slug":"exposing-query-identification-for-search","title":"Exposing Query Identification for Search Transparency","date":"2021-10-14","arxiv_id":"2110.07701","repositories_listed":0,"syntology":null},{"url":null,"slug":"representation-decoupling-for-open-domain","title":"Sentence-aware Contrastive Learning for Open-Domain Passage Retrieval","date":"2021-10-14","arxiv_id":"2110.07524","repositories_listed":0,"syntology":null},{"url":null,"slug":"retrieval-guided-counterfactual-generation","title":"Retrieval-guided Counterfactual Generation for QA","date":"2021-10-14","arxiv_id":"2110.07596","repositories_listed":0,"syntology":null},{"url":null,"slug":"tagged-documents-co-clustering","title":"Tagged Documents Co-Clustering","date":"2021-10-14","arxiv_id":"2110.11079","repositories_listed":0,"syntology":null},{"url":null,"slug":"zero-shot-dense-retrieval-with-momentum-1","title":"Zero-Shot Dense Retrieval with Momentum Adversarial Domain Invariant Representations","date":"2021-10-14","arxiv_id":"2110.07581","repositories_listed":0,"syntology":null},{"url":null,"slug":"color-counting-for-fashion-art-and-design","title":"Color Counting for Fashion, Art, and Design","date":"2021-10-13","arxiv_id":"2110.06682","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-users-mental-model-with-attention","title":"Improving Users' Mental Model with Attention-directed Counterfactual Edits","date":"2021-10-13","arxiv_id":"2110.06863","repositories_listed":0,"syntology":null},{"url":null,"slug":"winning-the-iccv-2021-value-challenge-task","title":"Winning the ICCV'2021 VALUE Challenge: Task-aware Ensemble and Transfer Learning with Visual Concepts","date":"2021-10-13","arxiv_id":"2110.06476","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-content-based-image-retrieval-for","title":"Exploring Content Based Image Retrieval for Highly Imbalanced Melanoma Data using Style Transfer, Semantic Image Segmentation and Ensemble Learning","date":"2021-10-12","arxiv_id":"2110.06331","repositories_listed":0,"syntology":null},{"url":null,"slug":"optimizing-ranking-systems-online-as-bandits","title":"Optimizing Ranking Systems Online as Bandits","date":"2021-10-12","arxiv_id":"2110.05807","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-recall-of-software-lessons-learned","title":"Automatic Recall of Software Lessons Learned for Software Project Managers","date":"2021-10-11","arxiv_id":"2110.05261","repositories_listed":0,"syntology":null},{"url":null,"slug":"viseret-a-simple-yet-effective-approach-to","title":"ViSeRet: A simple yet effective approach to moment retrieval via fine-grained video segmentation","date":"2021-10-11","arxiv_id":"2110.05146","repositories_listed":0,"syntology":null},{"url":null,"slug":"are-words-the-quanta-of-human-language","title":"Are Words the Quanta of Human Language? Extending the Domain of Quantum Cognition","date":"2021-10-10","arxiv_id":"2110.04913","repositories_listed":0,"syntology":null},{"url":null,"slug":"digging-into-self-supervised-learning-of","title":"Digging Into Self-Supervised Learning of Feature Descriptors","date":"2021-10-10","arxiv_id":"2110.04773","repositories_listed":0,"syntology":null},{"url":null,"slug":"fast-and-robust-structural-damage-analysis-of","title":"Fast and Robust Structural Damage Analysis of Civil Infrastructure Using UAV Imagery","date":"2021-10-10","arxiv_id":"2110.04806","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-feature-consistency-driven-attention","title":"A Feature Consistency Driven Attention Erasing Network for Fine-Grained Image Retrieval","date":"2021-10-09","arxiv_id":"2110.04479","repositories_listed":0,"syntology":null},{"url":null,"slug":"google-landmark-retrieval-2021-competition","title":"Google Landmark Retrieval 2021 Competition Third Place Solution","date":"2021-10-09","arxiv_id":"2110.04619","repositories_listed":0,"syntology":null},{"url":null,"slug":"cheerbots-chatbots-toward-empathy-and","title":"CheerBots: Chatbots toward Empathy and Emotionusing Reinforcement Learning","date":"2021-10-08","arxiv_id":"2110.03949","repositories_listed":0,"syntology":null},{"url":null,"slug":"kg-fid-infusing-knowledge-graph-in-fusion-in-1","title":"KG-FiD: Infusing Knowledge Graph in Fusion-in-Decoder for Open-Domain Question Answering","date":"2021-10-08","arxiv_id":"2110.04330","repositories_listed":0,"syntology":null},{"url":null,"slug":"gesera-general-domain-summary-evaluation-by","title":"GeSERA: General-domain Summary Evaluation by Relevance Analysis","date":"2021-10-07","arxiv_id":"2110.03567","repositories_listed":0,"syntology":null},{"url":null,"slug":"3rd-place-solution-to-google-landmark-1","title":"3rd Place Solution to Google Landmark Recognition Competition 2021","date":"2021-10-06","arxiv_id":"2110.02794","repositories_listed":0,"syntology":null},{"url":null,"slug":"reversible-adversarial-examples-against-local","title":"Reversible Attack based on Local Visual Adversarial Perturbation","date":"2021-10-06","arxiv_id":"2110.02700","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-survey-on-neural-word-embeddings","title":"A Survey On Neural Word Embeddings","date":"2021-10-05","arxiv_id":"2110.01804","repositories_listed":0,"syntology":null},{"url":null,"slug":"analyzing-the-impact-of-covid-19-on-economy","title":"Analyzing the Impact of COVID-19 on Economy from the Perspective of Users Reviews","date":"2021-10-05","arxiv_id":"2110.02198","repositories_listed":0,"syntology":null},{"url":null,"slug":"teach-me-what-to-say-and-i-will-learn-what-to","title":"Teach Me What to Say and I Will Learn What to Pick: Unsupervised Knowledge Selection Through Response Generation with Pretrained Generative Models","date":"2021-10-05","arxiv_id":"2110.02067","repositories_listed":0,"syntology":null},{"url":null,"slug":"voice-information-retrieval-in-collaborative","title":"Voice Information Retrieval In Collaborative Information Seeking","date":"2021-10-05","arxiv_id":"2110.01788","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-proposed-conceptual-framework-for-a","title":"A Proposed Conceptual Framework for a Representational Approach to Information Retrieval","date":"2021-10-04","arxiv_id":"2110.01529","repositories_listed":0,"syntology":null},{"url":null,"slug":"encoder-adaptation-of-dense-passage-retrieval","title":"Encoder Adaptation of Dense Passage Retrieval for Open-Domain Question Answering","date":"2021-10-04","arxiv_id":"2110.01599","repositories_listed":0,"syntology":null},{"url":null,"slug":"lawsum-a-weakly-supervised-approach-for","title":"LawSum: A weakly supervised approach for Indian Legal Document Summarization","date":"2021-10-04","arxiv_id":"2110.01188","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-structural-representations-for","title":"Learning Structural Representations for Recipe Generation and Food Retrieval","date":"2021-10-04","arxiv_id":"2110.01209","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-neural-matching-models-for-graph","title":"Matching Models for Graph Retrieval","date":"2021-10-03","arxiv_id":"2110.00925","repositories_listed":0,"syntology":null},{"url":null,"slug":"sdr-efficient-neural-re-ranking-using","title":"SDR: Efficient Neural Re-ranking using Succinct Document Representation","date":"2021-10-03","arxiv_id":"2110.02065","repositories_listed":0,"syntology":null},{"url":null,"slug":"spatio-temporal-video-representation-learning","title":"Spatio-Temporal Video Representation Learning for AI Based Video Playback Style Prediction","date":"2021-10-03","arxiv_id":"2110.01015","repositories_listed":0,"syntology":null},{"url":null,"slug":"tao-a-learning-framework-for-adaptive-nearest","title":"Tao: A Learning Framework for Adaptive Nearest Neighbor Search using Static Features Only","date":"2021-10-02","arxiv_id":"2110.00696","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-bert-based-siamese-structured-retrieval","title":"A BERT-based Siamese-structured Retrieval Model","date":"2021-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-study-on-using-transfer-learning-to-improve","title":"A Study on Using Transfer Learning to Improve BERT Model for Emotional Classification of Chinese Lyrics","date":"2021-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"building-an-efficient-and-effective-retrieval","title":"Building an Efficient and Effective Retrieval-based Dialogue System via Mutual Learning","date":"2021-10-01","arxiv_id":"2110.00159","repositories_listed":0,"syntology":null},{"url":null,"slug":"factored-couplings-in-multi-marginal-optimal","title":"Factored couplings in multi-marginal optimal transport via difference of convex programming","date":"2021-10-01","arxiv_id":"2110.00629","repositories_listed":0,"syntology":null},{"url":null,"slug":"video-temporal-relationship-mining-for-data","title":"Video Temporal Relationship Mining for Data-Efficient Person Re-identification","date":"2021-10-01","arxiv_id":"2110.00549","repositories_listed":0,"syntology":null},{"url":null,"slug":"assessing-algorithmic-biases-for-musical","title":"Assessing Algorithmic Biases for Musical Version Identification","date":"2021-09-30","arxiv_id":"2109.15188","repositories_listed":0,"syntology":null},{"url":null,"slug":"crossclr-cross-modal-contrastive-learning-for","title":"CrossCLR: Cross-modal Contrastive Learning For Multi-modal Video Representations","date":"2021-09-30","arxiv_id":"2109.14910","repositories_listed":0,"syntology":null},{"url":null,"slug":"library-of-congress-subject-heading-lcsh","title":"Library of Congress Subject Heading (LCSH) Browsing and Natural Language Searching","date":"2021-09-30","arxiv_id":"2109.15276","repositories_listed":0,"syntology":null},{"url":null,"slug":"adaptive-region-pooling-for-fine-grained","title":"Adaptive Region Pooling for Fine-Grained Representation Learning","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"asap-dml-deep-metric-learning-with","title":"ASAP DML: Deep Metric Learning with Alternating Sets of Alternating Proxies","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"calibrating-probabilistic-embeddings-for","title":"Calibrating Probabilistic Embeddings for Cross-Modal Retrieval","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"contrastive-learning-of-3d-shape-descriptor","title":"Contrastive Learning of 3D Shape Descriptor with Dynamic Adversarial Views","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"contrastive-pre-training-for-zero-shot","title":"Contrastive Pre-training for Zero-Shot Information Retrieval","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-fusion-of-multi-attentive-local-and","title":"Deep Fusion of Multi-attentive Local and Global Features with Higher Efficiency for Image Retrieval","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"dictionary-learning-under-generative","title":"Dictionary Learning Under Generative Coefficient Priors with Applications to Compression","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"from-graph-local-embedding-to-deep-metric","title":"From Graph Local Embedding to Deep Metric Learning","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"generating-scenes-with-latent-object-models","title":"Generating Scenes with Latent Object Models","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"graph-based-nearest-neighbor-search-in","title":"Graph-based Nearest Neighbor Search in Hyperbolic Spaces","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"graph-similarities-and-dual-approach-for","title":"Graph Similarities and Dual Approach for Sequential Text-to-Image Retrieval","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"hot-refresh-model-upgrades-with-regression","title":"Hot-Refresh Model Upgrades with Regression-Free Compatible Training in Image Retrieval","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"in-defense-of-dual-encoders-for-neural","title":"In defense of dual-encoders for neural ranking","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"inductive-biases-for-contrastive-learning-of","title":"Inductive-Biases for Contrastive Learning of Disentangled Representations","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"interest-based-item-representation-framework","title":"Interest-based Item Representation Framework for Recommendation with Multi-Interests Capsule Network","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"kimera-injecting-domain-knowledge-into-vacant","title":"KIMERA: Injecting Domain Knowledge into Vacant Transformer Heads","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"learned-index-with-dynamic-epsilon","title":"Learned Index with Dynamic $\\epsilon$","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-context-adapted-video-text-retrieval","title":"Learning Context-Adapted Video-Text Retrieval by Attending to User Comments","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"neurosed-learning-subgraph-similarity-via","title":"NeuroSED: Learning Subgraph Similarity via Graph Neural Networks","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"rank4class-examining-multiclass","title":"Rank4Class: Examining Multiclass Classification through the Lens of Learning to Rank","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"regularized-autoencoders-for-isometric","title":"Regularized Autoencoders for Isometric Representation Learning","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"revisiting-locality-sensitive-binary-codes","title":"Revisiting Locality-Sensitive Binary Codes from Random Fourier Features","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"self-supervised-modality-invariant-and","title":"Self-Supervised Modality-Invariant and Modality-Specific Feature Learning for 3D Objects","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"seq2tok-deep-sequence-tokenizer-for-retrieval","title":"Seq2Tok: Deep Sequence Tokenizer for Retrieval","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"short-term-memory-in-neural-language-models","title":"Short-term memory in neural language models","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null}],"record_sha256":"c41d248bef42e8294325aac415903663e0c0e73355b227d515e6bde1ca33dea4","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}