{"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":"/method/align/papers/49","list_of":"/method/align","method":"ALIGN","archive":{"snapshot":"2025-07-28"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"date (newest first), then slug","page":49,"pages_in_order":56,"rows_per_page":100,"rows":[4801,4900],"of":5524,"counts":{"archive_papers_tagged":5527,"with_a_code_link":2162,"where_syntology_ran_a_sample":726,"not_listed_spam_title":3,"listed":5524,"listed_where_code_ran":726,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":628,"every_run_a_failure_of_syntologys_instrument":98,"listed_with_a_run_with_no_instrument_failure":628,"listed_every_run_a_failure_of_syntologys_instrument":98,"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":"/method/align","prev":"/method/align/papers/48","next":"/method/align/papers/50","papers":[{"paper":null,"slug":"medgen3d-a-deep-generative-framework-for","title":"MedGen3D: A Deep Generative Framework for Paired 3D Image and Mask Generation","date":"2023-04-08","arxiv_id":"2304.04106","n_code_links":0,"syntology":null},{"paper":"/paper/dualrefine-self-supervised-depth-and-pose","slug":"dualrefine-self-supervised-depth-and-pose","title":"DualRefine: Self-Supervised Depth and Pose Estimation Through Iterative Epipolar Sampling and Refinement Toward Equilibrium","date":"2023-04-07","arxiv_id":"2304.03560","n_code_links":2,"syntology":{"ran":9,"of":12,"n_ran_checked":9,"n_instrument":0,"unverified":3,"pointer_only":12,"phrase":"9 ran (of which 8 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 0 violated, 9 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","official":{"repos":["antabangun/dualrefine"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/infoctm-a-mutual-information-maximization","slug":"infoctm-a-mutual-information-maximization","title":"InfoCTM: A Mutual Information Maximization Perspective of Cross-Lingual Topic Modeling","date":"2023-04-07","arxiv_id":"2304.03544","n_code_links":2,"syntology":{"ran":4,"of":5,"n_ran_checked":4,"n_instrument":0,"unverified":1,"pointer_only":2,"phrase":"4 ran (of which 2 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","official":{"repos":["bobxwu/infoctm"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"paper":null,"slug":"on-the-importance-of-contrastive-loss-in","title":"On the Importance of Contrastive Loss in Multimodal Learning","date":"2023-04-07","arxiv_id":"2304.03717","n_code_links":0,"syntology":null},{"paper":"/paper/privacy-preserving-cnn-training-with-transfer","slug":"privacy-preserving-cnn-training-with-transfer","title":"Privacy-Preserving CNN Training with Transfer Learning: Multiclass Logistic Regression","date":"2023-04-07","arxiv_id":"2304.03807","n_code_links":1,"syntology":null},{"paper":null,"slug":"capot-creating-robust-dense-query-encoders","title":"Noise-Robust Dense Retrieval via Contrastive Alignment Post Training","date":"2023-04-06","arxiv_id":"2304.03401","n_code_links":0,"syntology":null},{"paper":"/paper/implicit-anatomical-rendering-for-medical","slug":"implicit-anatomical-rendering-for-medical","title":"Implicit Anatomical Rendering for Medical Image Segmentation with Stochastic Experts","date":"2023-04-06","arxiv_id":"2304.03209","n_code_links":1,"syntology":null},{"paper":"/paper/ntk-sap-improving-neural-network-pruning-by","slug":"ntk-sap-improving-neural-network-pruning-by","title":"NTK-SAP: Improving neural network pruning by aligning training dynamics","date":"2023-04-06","arxiv_id":"2304.02840","n_code_links":1,"syntology":{"ran":0,"of":2,"n_ran_checked":0,"n_instrument":0,"unverified":2,"pointer_only":0,"phrase":"0 ran · 2 unverified","official":{"repos":["yitewang/ntk-sap"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":[]}}},{"paper":null,"slug":"pragmatically-appropriate-diversity-for","title":"Pragmatically Appropriate Diversity for Dialogue Evaluation","date":"2023-04-06","arxiv_id":"2304.02812","n_code_links":0,"syntology":null},{"paper":"/paper/high-fidelity-pseudo-labels-for-boosting","slug":"high-fidelity-pseudo-labels-for-boosting","title":"High-fidelity Pseudo-labels for Boosting Weakly-Supervised Segmentation","date":"2023-04-05","arxiv_id":"2304.02621","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-data-fusion-framework-for-multi-domain","title":"A Data Fusion Framework for Multi-Domain Morality Learning","date":"2023-04-04","arxiv_id":"2304.02144","n_code_links":0,"syntology":null},{"paper":null,"slug":"an-interpretability-framework-for-similar","title":"An interpretability framework for Similar case matching","date":"2023-04-04","arxiv_id":"2304.01622","n_code_links":0,"syntology":null},{"paper":"/paper/black-box-few-shot-adaptation-for-vision","slug":"black-box-few-shot-adaptation-for-vision","title":"Black Box Few-Shot Adaptation for Vision-Language models","date":"2023-04-04","arxiv_id":"2304.01752","n_code_links":1,"syntology":{"ran":0,"of":1,"n_ran_checked":0,"n_instrument":0,"unverified":1,"pointer_only":1,"phrase":"0 ran · 1 unverified","official":{"repos":["saic-fi/lfa"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":[]}}},{"paper":null,"slug":"learning-invariant-representation-via","title":"Learning Invariant Representation via Contrastive Feature Alignment for Clutter Robust SAR Target Recognition","date":"2023-04-04","arxiv_id":"2304.01747","n_code_links":0,"syntology":null},{"paper":null,"slug":"safe-explicable-robot-planning","title":"Safe Explicable Planning","date":"2023-04-04","arxiv_id":"2304.03773","n_code_links":0,"syntology":null},{"paper":"/paper/burstormer-burst-image-restoration-and","slug":"burstormer-burst-image-restoration-and","title":"Burstormer: Burst Image Restoration and Enhancement Transformer","date":"2023-04-03","arxiv_id":"2304.01194","n_code_links":2,"syntology":null},{"paper":"/paper/learning-similarity-between-scene-graphs-and","slug":"learning-similarity-between-scene-graphs-and","title":"SPAN: Learning Similarity between Scene Graphs and Images with Transformers","date":"2023-04-02","arxiv_id":"2304.00590","n_code_links":1,"syntology":null},{"paper":"/paper/jacobinerf-nerf-shaping-with-mutual","slug":"jacobinerf-nerf-shaping-with-mutual","title":"JacobiNeRF: NeRF Shaping with Mutual Information Gradients","date":"2023-04-01","arxiv_id":"2304.00341","n_code_links":1,"syntology":null},{"paper":null,"slug":"dime-fm-distilling-multimodal-and-efficient","title":"DIME-FM: DIstilling Multimodal and Efficient Foundation Models","date":"2023-03-31","arxiv_id":"2303.18232","n_code_links":0,"syntology":null},{"paper":"/paper/knn-res-residual-neural-network-with-knn","slug":"knn-res-residual-neural-network-with-knn","title":"kNN-Res: Residual Neural Network with kNN-Graph coherence for point cloud registration","date":"2023-03-31","arxiv_id":"2304.00050","n_code_links":1,"syntology":null},{"paper":null,"slug":"semhint-md-learning-from-noisy-semantic","title":"SemHint-MD: Learning from Noisy Semantic Labels for Self-Supervised Monocular Depth Estimation","date":"2023-03-31","arxiv_id":"2303.18219","n_code_links":0,"syntology":null},{"paper":null,"slug":"aligning-a-medium-size-gpt-model-in-english","title":"Aligning a medium-size GPT model in English to a small closed domain in Spanish","date":"2023-03-30","arxiv_id":"2303.17649","n_code_links":0,"syntology":null},{"paper":null,"slug":"dae-talker-high-fidelity-speech-driven","title":"DAE-Talker: High Fidelity Speech-Driven Talking Face Generation with Diffusion Autoencoder","date":"2023-03-30","arxiv_id":"2303.17550","n_code_links":0,"syntology":null},{"paper":null,"slug":"sound-to-visual-scene-generation-by-audio-to","title":"Sound to Visual Scene Generation by Audio-to-Visual Latent Alignment","date":"2023-03-30","arxiv_id":"2303.17490","n_code_links":0,"syntology":null},{"paper":null,"slug":"task-oriented-multi-modal-mutual-leaning-for","title":"Task-Oriented Multi-Modal Mutual Leaning for Vision-Language Models","date":"2023-03-30","arxiv_id":"2303.17169","n_code_links":0,"syntology":null},{"paper":null,"slug":"using-ai-to-measure-parkinson-s-disease","title":"Using AI to Measure Parkinson's Disease Severity at Home","date":"2023-03-30","arxiv_id":"2303.17573","n_code_links":0,"syntology":null},{"paper":null,"slug":"what-types-of-questions-require-conversation","title":"What Types of Questions Require Conversation to Answer? A Case Study of AskReddit Questions","date":"2023-03-30","arxiv_id":"2303.17710","n_code_links":0,"syntology":null},{"paper":"/paper/global-adaptation-meets-local-generalization","slug":"global-adaptation-meets-local-generalization","title":"Global Adaptation meets Local Generalization: Unsupervised Domain Adaptation for 3D Human Pose Estimation","date":"2023-03-29","arxiv_id":"2303.16456","n_code_links":1,"syntology":null},{"paper":null,"slug":"towards-understanding-the-effect-of","title":"Towards Understanding the Effect of Pretraining Label Granularity","date":"2023-03-29","arxiv_id":"2303.16887","n_code_links":0,"syntology":null},{"paper":null,"slug":"urgency-aware-routing-in-single-origin","title":"Urgency-aware Routing in Single Origin-destination Itineraries through Artificial Currencies","date":"2023-03-29","arxiv_id":"2303.16945","n_code_links":0,"syntology":null},{"paper":null,"slug":"unify-align-and-refine-multi-level-semantic","title":"Unify, Align and Refine: Multi-Level Semantic Alignment for Radiology Report Generation","date":"2023-03-28","arxiv_id":"2303.15932","n_code_links":0,"syntology":null},{"paper":"/paper/unmasked-teacher-towards-training-efficient","slug":"unmasked-teacher-towards-training-efficient","title":"Unmasked Teacher: Towards Training-Efficient Video Foundation Models","date":"2023-03-28","arxiv_id":"2303.16058","n_code_links":1,"syntology":{"ran":8,"of":8,"n_ran_checked":7,"n_instrument":1,"unverified":0,"pointer_only":3,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 1 honoured, 0 violated, 6 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["opengvlab/unmasked_teacher"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"variational-distribution-learning-for","title":"Variational Distribution Learning for Unsupervised Text-to-Image Generation","date":"2023-03-28","arxiv_id":"2303.16105","n_code_links":0,"syntology":null},{"paper":"/paper/eegmatch-learning-with-incomplete-labels-for","slug":"eegmatch-learning-with-incomplete-labels-for","title":"EEGMatch: Learning with Incomplete Labels for Semi-Supervised EEG-based Cross-Subject Emotion Recognition","date":"2023-03-27","arxiv_id":"2304.06496","n_code_links":1,"syntology":null},{"paper":null,"slug":"empowering-dual-encoder-with-query-generator","title":"Empowering Dual-Encoder with Query Generator for Cross-Lingual Dense Retrieval","date":"2023-03-27","arxiv_id":"2303.14991","n_code_links":0,"syntology":null},{"paper":null,"slug":"global-relation-modeling-and-refinement-for","title":"Global Relation Modeling and Refinement for Bottom-Up Human Pose Estimation","date":"2023-03-27","arxiv_id":"2303.14888","n_code_links":0,"syntology":null},{"paper":"/paper/kpeval-towards-fine-grained-semantic-based","slug":"kpeval-towards-fine-grained-semantic-based","title":"KPEval: Towards Fine-Grained Semantic-Based Keyphrase Evaluation","date":"2023-03-27","arxiv_id":"2303.15422","n_code_links":1,"syntology":null},{"paper":"/paper/unidistill-a-universal-cross-modality","slug":"unidistill-a-universal-cross-modality","title":"UniDistill: A Universal Cross-Modality Knowledge Distillation Framework for 3D Object Detection in Bird's-Eye View","date":"2023-03-27","arxiv_id":"2303.15083","n_code_links":1,"syntology":{"ran":3,"of":3,"n_ran_checked":2,"n_instrument":1,"unverified":0,"pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 2 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["megvii-research/cvpr2023-unidistill"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/sem-pos-grammatically-and-semantically","slug":"sem-pos-grammatically-and-semantically","title":"SEM-POS: Grammatically and Semantically Correct Video Captioning","date":"2023-03-26","arxiv_id":"2303.14829","n_code_links":0,"syntology":null},{"paper":null,"slug":"semantic-neural-decoding-via-cross-modal","title":"Joint fMRI Decoding and Encoding with Latent Embedding Alignment","date":"2023-03-26","arxiv_id":"2303.14730","n_code_links":0,"syntology":null},{"paper":"/paper/better-aligning-text-to-image-models-with","slug":"better-aligning-text-to-image-models-with","title":"Human Preference Score: Better Aligning Text-to-Image Models with Human Preference","date":"2023-03-25","arxiv_id":"2303.14420","n_code_links":1,"syntology":{"ran":3,"of":4,"n_ran_checked":3,"n_instrument":0,"unverified":1,"pointer_only":1,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","official":{"repos":["tgxs002/align_sd"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/bridging-precision-and-confidence-a-train","slug":"bridging-precision-and-confidence-a-train","title":"Bridging Precision and Confidence: A Train-Time Loss for Calibrating Object Detection","date":"2023-03-25","arxiv_id":"2303.14404","n_code_links":1,"syntology":{"ran":12,"of":18,"n_ran_checked":4,"n_instrument":8,"unverified":6,"pointer_only":1,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 3 honoured, 1 violated, 0 with no contract checked; 8 where Syntology's instrument failed) · 6 unverified","official":{"repos":["akhtarvision/bpc_calibration"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":6,"ran_from_kinds":["official","unlocated"]}}},{"paper":"/paper/deepvecfont-v2-exploiting-transformers-to","slug":"deepvecfont-v2-exploiting-transformers-to","title":"DeepVecFont-v2: Exploiting Transformers to Synthesize Vector Fonts with Higher Quality","date":"2023-03-25","arxiv_id":"2303.14585","n_code_links":1,"syntology":null},{"paper":null,"slug":"factor-decomposed-generative-adversarial","title":"Factor Decomposed Generative Adversarial Networks for Text-to-Image Synthesis","date":"2023-03-24","arxiv_id":"2303.13821","n_code_links":0,"syntology":null},{"paper":"/paper/gp-vton-towards-general-purpose-virtual-try","slug":"gp-vton-towards-general-purpose-virtual-try","title":"GP-VTON: Towards General Purpose Virtual Try-on via Collaborative Local-Flow Global-Parsing Learning","date":"2023-03-24","arxiv_id":"2303.13756","n_code_links":2,"syntology":null},{"paper":"/paper/inherent-consistent-learning-for-accurate","slug":"inherent-consistent-learning-for-accurate","title":"Inherent Consistent Learning for Accurate Semi-supervised Medical Image Segmentation","date":"2023-03-24","arxiv_id":"2303.14175","n_code_links":2,"syntology":null},{"paper":"/paper/k-nn-prompting-beyond-context-learning-with","slug":"k-nn-prompting-beyond-context-learning-with","title":"$k$NN Prompting: Beyond-Context Learning with Calibration-Free Nearest Neighbor Inference","date":"2023-03-24","arxiv_id":"2303.13824","n_code_links":1,"syntology":{"ran":1,"of":4,"n_ran_checked":1,"n_instrument":0,"unverified":3,"pointer_only":4,"phrase":"1 ran (of which 1 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified; the one sample that ran constructed an object rather than computing a result","official":{"repos":["benfengxu/knnprompting"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"minddiffuser-controlled-image-reconstruction","title":"MindDiffuser: Controlled Image Reconstruction from Human Brain Activity with Semantic and Structural Diffusion","date":"2023-03-24","arxiv_id":"2303.14139","n_code_links":0,"syntology":null},{"paper":null,"slug":"unsupervised-hierarchical-domain-adaptation","title":"Unsupervised Hierarchical Domain Adaptation for Adverse Weather Optical Flow","date":"2023-03-24","arxiv_id":"2303.13761","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-simple-and-generic-framework-for-feature","title":"A Simple and Generic Framework for Feature Distillation via Channel-wise Transformation","date":"2023-03-23","arxiv_id":"2303.13212","n_code_links":0,"syntology":null},{"paper":"/paper/dare-gram-unsupervised-domain-adaptation","slug":"dare-gram-unsupervised-domain-adaptation","title":"DARE-GRAM : Unsupervised Domain Adaptation Regression by Aligning Inverse Gram Matrices","date":"2023-03-23","arxiv_id":"2303.13325","n_code_links":1,"syntology":{"ran":0,"of":1,"n_ran_checked":0,"n_instrument":0,"unverified":1,"pointer_only":0,"phrase":"0 ran · 1 unverified","official":{"repos":["ismailnejjar/dare-gram"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":[]}}},{"paper":null,"slug":"judicial-intelligent-assistant-system","title":"Judicial Intelligent Assistant System: Extracting Events from Divorce Cases to Detect Disputes for the Judge","date":"2023-03-23","arxiv_id":"2303.16751","n_code_links":0,"syntology":null},{"paper":null,"slug":"magicfusion-boosting-text-to-image-generation","title":"MagicFusion: Boosting Text-to-Image Generation Performance by Fusing Diffusion Models","date":"2023-03-23","arxiv_id":"2303.13126","n_code_links":0,"syntology":null},{"paper":"/paper/taps3d-text-guided-3d-textured-shape","slug":"taps3d-text-guided-3d-textured-shape","title":"TAPS3D: Text-Guided 3D Textured Shape Generation from Pseudo Supervision","date":"2023-03-23","arxiv_id":"2303.13273","n_code_links":1,"syntology":null},{"paper":null,"slug":"three-ways-to-improve-feature-alignment-for","title":"Three ways to improve feature alignment for open vocabulary detection","date":"2023-03-23","arxiv_id":"2303.13518","n_code_links":0,"syntology":null},{"paper":"/paper/cross-modal-implicit-relation-reasoning-and","slug":"cross-modal-implicit-relation-reasoning-and","title":"Cross-Modal Implicit Relation Reasoning and Aligning for Text-to-Image Person Retrieval","date":"2023-03-22","arxiv_id":"2303.12501","n_code_links":1,"syntology":{"ran":5,"of":9,"n_ran_checked":4,"n_instrument":1,"unverified":4,"pointer_only":0,"phrase":"5 ran (of which 3 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 1 where Syntology's instrument failed) · 4 unverified","official":{"repos":["anosorae/irra"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":3,"n_ran_no_instrument_failure":4,"n_unverified":4,"ran_from_kinds":["official"]}}},{"paper":"/paper/tifa-accurate-and-interpretable-text-to-image","slug":"tifa-accurate-and-interpretable-text-to-image","title":"TIFA: Accurate and Interpretable Text-to-Image Faithfulness Evaluation with Question Answering","date":"2023-03-21","arxiv_id":"2303.11897","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["Yushi-Hu/tifa"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/tma-temporal-motion-aggregation-for-event","slug":"tma-temporal-motion-aggregation-for-event","title":"TMA: Temporal Motion Aggregation for Event-based Optical Flow","date":"2023-03-21","arxiv_id":"2303.11629","n_code_links":1,"syntology":{"ran":12,"of":13,"n_ran_checked":10,"n_instrument":2,"unverified":1,"pointer_only":13,"phrase":"12 ran (of which 7 constructed an object rather than computing a result; 10 with no instrument failure: 1 honoured, 0 violated, 9 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","official":{"repos":["ispc-lab/tma"],"state":"official (archive's flag): 12 ran","n_ran":12,"n_constructed":7,"n_ran_no_instrument_failure":10,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/a-dual-branch-self-supervised-representation","slug":"a-dual-branch-self-supervised-representation","title":"A Dual-branch Self-supervised Representation Learning Framework for Tumour Segmentation in Whole Slide Images","date":"2023-03-20","arxiv_id":"2303.11019","n_code_links":2,"syntology":null},{"paper":"/paper/clip-goes-3d-leveraging-prompt-tuning-for","slug":"clip-goes-3d-leveraging-prompt-tuning-for","title":"CLIP goes 3D: Leveraging Prompt Tuning for Language Grounded 3D Recognition","date":"2023-03-20","arxiv_id":"2303.11313","n_code_links":1,"syntology":null},{"paper":"/paper/feature-alignment-and-uniformity-for-test","slug":"feature-alignment-and-uniformity-for-test","title":"Feature Alignment and Uniformity for Test Time Adaptation","date":"2023-03-20","arxiv_id":"2303.10902","n_code_links":1,"syntology":{"ran":2,"of":3,"n_ran_checked":1,"n_instrument":1,"unverified":1,"pointer_only":0,"phrase":"2 ran (of which 1 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","official":{"repos":["sakurajimamaiii/tsd"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"model-free-hedging-of-impermanent-loss-in","title":"Model-free Hedging of Impermanent Loss in Geometric Mean Market Makers","date":"2023-03-20","arxiv_id":"2303.11118","n_code_links":0,"syntology":null},{"paper":null,"slug":"unsupervised-cross-domain-rumor-detection","title":"Unsupervised Cross-Domain Rumor Detection with Contrastive Learning and Cross-Attention","date":"2023-03-20","arxiv_id":"2303.11945","n_code_links":0,"syntology":null},{"paper":null,"slug":"just-noticeable-visual-redundancy-forecasting","title":"Just Noticeable Visual Redundancy Forecasting: A Deep Multimodal-driven Approach","date":"2023-03-18","arxiv_id":"2303.10372","n_code_links":0,"syntology":null},{"paper":"/paper/a-unified-continual-learning-framework-with","slug":"a-unified-continual-learning-framework-with","title":"A Unified Continual Learning Framework with General Parameter-Efficient Tuning","date":"2023-03-17","arxiv_id":"2303.10070","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":2,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"2 ran (of which 2 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; every one of the 2 samples that ran constructed an object rather than computing a result","official":{"repos":["gqk/lae"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":2,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"generate-transform-answer-question-specific","title":"Generate, Transform, Answer: Question Specific Tool Synthesis for Tabular Data","date":"2023-03-17","arxiv_id":"2303.10138","n_code_links":0,"syntology":null},{"paper":"/paper/gluegen-plug-and-play-multi-modal-encoders","slug":"gluegen-plug-and-play-multi-modal-encoders","title":"GlueGen: Plug and Play Multi-modal Encoders for X-to-image Generation","date":"2023-03-17","arxiv_id":"2303.10056","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":2,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"2 ran (of which 2 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; every one of the 2 samples that ran constructed an object rather than computing a result","official":{"repos":["salesforce/gluegen"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":2,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"morf-mobile-realistic-fullbody-avatars-from-a","title":"MoRF: Mobile Realistic Fullbody Avatars from a Monocular Video","date":"2023-03-17","arxiv_id":"2303.10275","n_code_links":0,"syntology":null},{"paper":null,"slug":"facial-affect-recognition-based-on","title":"Facial Affect Recognition based on Transformer Encoder and Audiovisual Fusion for the ABAW5 Challenge","date":"2023-03-16","arxiv_id":"2303.09158","n_code_links":0,"syntology":null},{"paper":"/paper/hive-harnessing-human-feedback-for","slug":"hive-harnessing-human-feedback-for","title":"HIVE: Harnessing Human Feedback for Instructional Visual Editing","date":"2023-03-16","arxiv_id":"2303.09618","n_code_links":1,"syntology":{"ran":3,"of":4,"n_ran_checked":2,"n_instrument":1,"unverified":1,"pointer_only":2,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 2 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","official":{"repos":["salesforce/HIVE"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"towards-the-scalable-evaluation-of","title":"Towards the Scalable Evaluation of Cooperativeness in Language Models","date":"2023-03-16","arxiv_id":"2303.13360","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-study-on-bias-and-fairness-in-deep-speaker","title":"A Study on Bias and Fairness In Deep Speaker Recognition","date":"2023-03-14","arxiv_id":"2303.08026","n_code_links":0,"syntology":null},{"paper":null,"slug":"gann-graph-alignment-neural-network-for-semi","title":"GANN: Graph Alignment Neural Network for Semi-Supervised Learning","date":"2023-03-14","arxiv_id":"2303.07778","n_code_links":0,"syntology":null},{"paper":null,"slug":"localizing-spatial-information-in-neural","title":"Localizing Spatial Information in Neural Spatiospectral Filters","date":"2023-03-14","arxiv_id":"2303.08052","n_code_links":0,"syntology":null},{"paper":"/paper/neuro-symbolic-commonsense-social-reasoning","slug":"neuro-symbolic-commonsense-social-reasoning","title":"Neuro-symbolic Commonsense Social Reasoning","date":"2023-03-14","arxiv_id":"2303.08264","n_code_links":3,"syntology":null},{"paper":"/paper/pimae-point-cloud-and-image-interactive","slug":"pimae-point-cloud-and-image-interactive","title":"PiMAE: Point Cloud and Image Interactive Masked Autoencoders for 3D Object Detection","date":"2023-03-14","arxiv_id":"2303.08129","n_code_links":1,"syntology":{"ran":3,"of":5,"n_ran_checked":3,"n_instrument":0,"unverified":2,"pointer_only":5,"phrase":"3 ran (of which 3 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified; every one of the 3 samples that ran constructed an object rather than computing a result","official":{"repos":["blvlab/pimae"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":3,"n_ran_no_instrument_failure":3,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/align-and-attend-multimodal-summarization","slug":"align-and-attend-multimodal-summarization","title":"Align and Attend: Multimodal Summarization with Dual Contrastive Losses","date":"2023-03-13","arxiv_id":"2303.07284","n_code_links":2,"syntology":null},{"paper":"/paper/lrbmat-a-novel-gut-microbial-interaction-and","slug":"lrbmat-a-novel-gut-microbial-interaction-and","title":"LRBmat: A Novel Gut Microbial Interaction and Individual Heterogeneity Inference Method for Colorectal Cancer","date":"2023-03-13","arxiv_id":"2303.07498","n_code_links":1,"syntology":null},{"paper":"/paper/siamese-graph-learning-for-semi-supervised","slug":"siamese-graph-learning-for-semi-supervised","title":"Siamese Graph Learning for Semi-supervised Age Estimation","date":"2023-03-13","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/use-perturbations-when-learning-from-1","slug":"use-perturbations-when-learning-from-1","title":"Use Perturbations when Learning from Explanations","date":"2023-03-11","arxiv_id":"2303.06419","n_code_links":1,"syntology":null},{"paper":"/paper/multi-efficient-video-and-language","slug":"multi-efficient-video-and-language","title":"MuLTI: Efficient Video-and-Language Understanding with Text-Guided MultiWay-Sampler and Multiple Choice Modeling","date":"2023-03-10","arxiv_id":"2303.05707","n_code_links":0,"syntology":null},{"paper":null,"slug":"mdaesf-cine-mri-reconstruction-based-on","title":"Reconstruction of Cardiac Cine MRI Using Motion-Guided Deformable Alignment and Multi-Resolution Fusion","date":"2023-03-09","arxiv_id":"2303.04968","n_code_links":0,"syntology":null},{"paper":"/paper/adversarial-modality-alignment-network-for","slug":"adversarial-modality-alignment-network-for","title":"Adversarial Modality Alignment Network for Cross-Modal Molecule Retrieval","date":"2023-03-08","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/enhancing-low-resolution-face-recognition","slug":"enhancing-low-resolution-face-recognition","title":"Enhancing Low-resolution Face Recognition with Feature Similarity Knowledge Distillation","date":"2023-03-08","arxiv_id":"2303.04681","n_code_links":1,"syntology":null},{"paper":null,"slug":"optimal-sparse-recovery-with-decision-stumps","title":"Optimal Sparse Recovery with Decision Stumps","date":"2023-03-08","arxiv_id":"2303.04301","n_code_links":0,"syntology":null},{"paper":null,"slug":"semantically-consistent-multi-view","title":"Semantically Consistent Multi-view Representation Learning","date":"2023-03-08","arxiv_id":"2303.04366","n_code_links":0,"syntology":null},{"paper":null,"slug":"adaptive-knowledge-distillation-between-text","title":"Adaptive Knowledge Distillation between Text and Speech Pre-trained Models","date":"2023-03-07","arxiv_id":"2303.03600","n_code_links":0,"syntology":null},{"paper":null,"slug":"data-games-a-game-theoretic-approach-to-swarm","title":"Data Games: A Game-Theoretic Approach to Swarm Robotic Data Collection","date":"2023-03-07","arxiv_id":"2303.03602","n_code_links":0,"syntology":null},{"paper":"/paper/dinet-deformation-inpainting-network-for","slug":"dinet-deformation-inpainting-network-for","title":"DINet: Deformation Inpainting Network for Realistic Face Visually Dubbing on High Resolution Video","date":"2023-03-07","arxiv_id":"2303.03988","n_code_links":1,"syntology":{"ran":2,"of":10,"n_ran_checked":1,"n_instrument":1,"unverified":8,"pointer_only":10,"phrase":"2 ran (of which 1 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 1 where Syntology's instrument failed) · 8 unverified","official":{"repos":["MRzzm/DINet"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":8,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"fit-frequency-based-image-translation-for","title":"FIT: Frequency-based Image Translation for Domain Adaptive Object Detection","date":"2023-03-07","arxiv_id":"2303.03698","n_code_links":0,"syntology":null},{"paper":null,"slug":"ifan-an-explainability-focused-interaction","title":"IFAN: An Explainability-Focused Interaction Framework for Humans and NLP Models","date":"2023-03-06","arxiv_id":"2303.03124","n_code_links":0,"syntology":null},{"paper":"/paper/learning-human-compatible-representations-for","slug":"learning-human-compatible-representations-for","title":"Learning Human-Compatible Representations for Case-Based Decision Support","date":"2023-03-06","arxiv_id":"2303.04809","n_code_links":1,"syntology":{"ran":3,"of":3,"n_ran_checked":0,"n_instrument":3,"unverified":0,"pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","official":{"repos":["chicagohai/learning-human-compatible-representations"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"ris-aided-wireless-communications-can-ris","title":"RIS-aided Wireless Communications: Can RIS Beat Metal Plate?","date":"2023-03-06","arxiv_id":"2303.02938","n_code_links":0,"syntology":null},{"paper":"/paper/finding-alignments-between-interpretable","slug":"finding-alignments-between-interpretable","title":"Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations","date":"2023-03-05","arxiv_id":"2303.02536","n_code_links":1,"syntology":null},{"paper":"/paper/mitfas-mutual-information-based-temporal","slug":"mitfas-mutual-information-based-temporal","title":"MITFAS: Mutual Information based Temporal Feature Alignment and Sampling for Aerial Video Action Recognition","date":"2023-03-05","arxiv_id":"2303.02575","n_code_links":1,"syntology":null},{"paper":null,"slug":"momentum-based-learning-of-nash-equilibria","title":"Momentum-Based Learning of Nash Equilibria for LISA Pointing Acquisition","date":"2023-03-05","arxiv_id":"2303.02743","n_code_links":0,"syntology":null},{"paper":"/paper/vtqa-visual-text-question-answering-via","slug":"vtqa-visual-text-question-answering-via","title":"VTQA: Visual Text Question Answering via Entity Alignment and Cross-Media Reasoning","date":"2023-03-05","arxiv_id":"2303.02635","n_code_links":1,"syntology":null},{"paper":null,"slug":"dataset-creation-pipeline-for-camera-based","title":"Dataset Creation Pipeline for Camera-Based Heart Rate Estimation","date":"2023-03-02","arxiv_id":"2303.01468","n_code_links":0,"syntology":null},{"paper":"/paper/dropout-reduces-underfitting","slug":"dropout-reduces-underfitting","title":"Dropout Reduces Underfitting","date":"2023-03-02","arxiv_id":"2303.01500","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["facebookresearch/dropout"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/geolab-geometry-based-tractography","slug":"geolab-geometry-based-tractography","title":"GeoLab: Geometry-based Tractography Parcellation of Superficial White Matter","date":"2023-03-02","arxiv_id":"2303.01147","n_code_links":1,"syntology":null}],"record_sha256":"faf1cc13e06c2d85f93fc6e1aae3dd1f8c7d3f2324a153117bc831963860e77c","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}