{"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/transformer/papers/86","list_of":"/method/transformer","method":"Transformer","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":86,"pages_in_order":140,"rows_per_page":100,"rows":[8501,8600],"of":13999,"counts":{"archive_papers_tagged":13999,"with_a_code_link":6572,"where_syntology_ran_a_sample":2248,"not_listed_spam_title":0,"listed":13999,"listed_where_code_ran":2248,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":1919,"every_run_a_failure_of_syntologys_instrument":329,"listed_with_a_run_with_no_instrument_failure":1919,"listed_every_run_a_failure_of_syntologys_instrument":329,"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/transformer","prev":"/method/transformer/papers/85","next":"/method/transformer/papers/87","papers":[{"paper":"/paper/minigpt-4-enhancing-vision-language","slug":"minigpt-4-enhancing-vision-language","title":"MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models","date":"2023-04-20","arxiv_id":"2304.10592","n_code_links":6,"syntology":null},{"paper":null,"slug":"optogpt-a-foundation-model-for-inverse-design","title":"OptoGPT: A Foundation Model for Inverse Design in Optical Multilayer Thin Film Structures","date":"2023-04-20","arxiv_id":"2304.10294","n_code_links":0,"syntology":null},{"paper":null,"slug":"performance-of-chatgpt-on-the-us-fundamentals","title":"Performance of ChatGPT on the US Fundamentals of Engineering Exam: Comprehensive Assessment of Proficiency and Potential Implications for Professional Environmental Engineering Practice","date":"2023-04-20","arxiv_id":"2304.12198","n_code_links":0,"syntology":null},{"paper":null,"slug":"recurrent-transformer-for-dynamic-graph","title":"Dynamic Graph Representation Learning via Edge Temporal States Modeling and Structure-reinforced Transformer","date":"2023-04-20","arxiv_id":"2304.10079","n_code_links":0,"syntology":null},{"paper":"/paper/safety-assessment-of-chinese-large-language","slug":"safety-assessment-of-chinese-large-language","title":"Safety Assessment of Chinese Large Language Models","date":"2023-04-20","arxiv_id":"2304.10436","n_code_links":2,"syntology":null},{"paper":"/paper/text2seg-remote-sensing-image-semantic","slug":"text2seg-remote-sensing-image-semantic","title":"Text2Seg: Remote Sensing Image Semantic Segmentation via Text-Guided Visual Foundation Models","date":"2023-04-20","arxiv_id":"2304.10597","n_code_links":1,"syntology":{"ran":3,"of":4,"n_ran_checked":3,"n_instrument":0,"unverified":1,"pointer_only":0,"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":["douglas2code/text2seg"],"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/chameleon-plug-and-play-compositional","slug":"chameleon-plug-and-play-compositional","title":"Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models","date":"2023-04-19","arxiv_id":"2304.09842","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":null}},{"paper":null,"slug":"cross-reference-transformer-for-few-shot","title":"Few-shot Medical Image Segmentation via Cross-Reference Transformer","date":"2023-04-19","arxiv_id":"2304.09630","n_code_links":0,"syntology":null},{"paper":"/paper/is-chatgpt-good-at-search-investigating-large","slug":"is-chatgpt-good-at-search-investigating-large","title":"Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking Agents","date":"2023-04-19","arxiv_id":"2304.09542","n_code_links":1,"syntology":null},{"paper":"/paper/learning-robust-visual-semantic-embedding-for","slug":"learning-robust-visual-semantic-embedding-for","title":"Learning Robust Visual-Semantic Embedding for Generalizable Person Re-identification","date":"2023-04-19","arxiv_id":"2304.09498","n_code_links":1,"syntology":null},{"paper":"/paper/lipsformer-introducing-lipschitz-continuity","slug":"lipsformer-introducing-lipschitz-continuity","title":"LipsFormer: Introducing Lipschitz Continuity to Vision Transformers","date":"2023-04-19","arxiv_id":"2304.09856","n_code_links":1,"syntology":{"ran":4,"of":7,"n_ran_checked":4,"n_instrument":0,"unverified":3,"pointer_only":0,"phrase":"4 ran (of which 4 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) · 3 unverified; every one of the 4 samples that ran constructed an object rather than computing a result","official":{"repos":["idea-research/lipsformer"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":4,"n_ran_no_instrument_failure":4,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":"/paper/pointerformer-deep-reinforced-multi-pointer","slug":"pointerformer-deep-reinforced-multi-pointer","title":"Pointerformer: Deep Reinforced Multi-Pointer Transformer for the Traveling Salesman Problem","date":"2023-04-19","arxiv_id":"2304.09407","n_code_links":2,"syntology":{"ran":2,"of":3,"n_ran_checked":0,"n_instrument":2,"unverified":1,"pointer_only":3,"phrase":"2 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; 2 where Syntology's instrument failed) · 1 unverified","official":{"repos":["Learning4Optimization-HUST/Pointerformer"],"state":"official: no sample here; runs from other or unrecorded repositories","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["named_in_paper"]}}},{"paper":"/paper/progressive-hint-prompting-improves-reasoning","slug":"progressive-hint-prompting-improves-reasoning","title":"Progressive-Hint Prompting Improves Reasoning in Large Language Models","date":"2023-04-19","arxiv_id":"2304.09797","n_code_links":1,"syntology":{"ran":3,"of":4,"n_ran_checked":0,"n_instrument":3,"unverified":1,"pointer_only":4,"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) · 1 unverified","official":{"repos":["chuanyang-Zheng/Progressive-Hint"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/scaling-transformer-to-1m-tokens-and-beyond","slug":"scaling-transformer-to-1m-tokens-and-beyond","title":"Scaling Transformer to 1M tokens and beyond with RMT","date":"2023-04-19","arxiv_id":"2304.11062","n_code_links":3,"syntology":{"ran":5,"of":8,"n_ran_checked":4,"n_instrument":1,"unverified":3,"pointer_only":1,"phrase":"5 ran (of which 0 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) · 3 unverified","official":{"repos":["booydar/t5-experiments"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":null,"slug":"a-neural-lambda-calculus-neurosymbolic-ai","title":"Towards a Neural Lambda Calculus: Neurosymbolic AI Applied to the Foundations of Functional Programming","date":"2023-04-18","arxiv_id":"2304.09276","n_code_links":0,"syntology":null},{"paper":null,"slug":"approximate-nearest-neighbour-phrase-mining","title":"Approximate Nearest Neighbour Phrase Mining for Contextual Speech Recognition","date":"2023-04-18","arxiv_id":"2304.08862","n_code_links":0,"syntology":null},{"paper":null,"slug":"exploring-the-trade-offs-unified-large","title":"Exploring the Trade-Offs: Unified Large Language Models vs Local Fine-Tuned Models for Highly-Specific Radiology NLI Task","date":"2023-04-18","arxiv_id":"2304.09138","n_code_links":0,"syntology":null},{"paper":null,"slug":"from-words-to-music-a-study-of-subword","title":"From Words to Music: A Study of Subword Tokenization Techniques in Symbolic Music Generation","date":"2023-04-18","arxiv_id":"2304.08953","n_code_links":0,"syntology":null},{"paper":null,"slug":"llms-can-generate-robotic-scripts-from-goal","title":"LLMs can generate robotic scripts from goal-oriented instructions in biological laboratory automation","date":"2023-04-18","arxiv_id":"2304.10267","n_code_links":0,"syntology":null},{"paper":"/paper/saliency-aware-stereoscopic-video-retargeting","slug":"saliency-aware-stereoscopic-video-retargeting","title":"Saliency-aware Stereoscopic Video Retargeting","date":"2023-04-18","arxiv_id":"2304.08852","n_code_links":1,"syntology":null},{"paper":null,"slug":"think-before-you-act-unified-policy-for","title":"Think Before You Act: Unified Policy for Interleaving Language Reasoning with Actions","date":"2023-04-18","arxiv_id":"2304.11063","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-question-answering-approach-to-key-value","title":"A Question-Answering Approach to Key Value Pair Extraction from Form-like Document Images","date":"2023-04-17","arxiv_id":"2304.07957","n_code_links":0,"syntology":null},{"paper":null,"slug":"an-in-depth-investigation-of-user-response","title":"An In-depth Investigation of User Response Simulation for Conversational Search","date":"2023-04-17","arxiv_id":"2304.07944","n_code_links":0,"syntology":null},{"paper":"/paper/attention-mixtures-for-time-aware-sequential","slug":"attention-mixtures-for-time-aware-sequential","title":"Attention Mixtures for Time-Aware Sequential Recommendation","date":"2023-04-17","arxiv_id":"2304.08158","n_code_links":1,"syntology":null},{"paper":null,"slug":"causality-aware-visual-scene-discovery-for","title":"VCD: Visual Causality Discovery for Cross-Modal Question Reasoning","date":"2023-04-17","arxiv_id":"2304.08083","n_code_links":0,"syntology":null},{"paper":null,"slug":"deep-learning-based-vascularture-extraction","title":"Deep-Learning-based Vasculature Extraction for Single-Scan Optical Coherence Tomography Angiography","date":"2023-04-17","arxiv_id":"2304.08282","n_code_links":0,"syntology":null},{"paper":"/paper/detrs-beat-yolos-on-real-time-object","slug":"detrs-beat-yolos-on-real-time-object","title":"DETRs Beat YOLOs on Real-time Object Detection","date":"2023-04-17","arxiv_id":"2304.08069","n_code_links":9,"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":["lyuwenyu/RT-DETR"],"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/efficient-and-effective-text-encoding-for","slug":"efficient-and-effective-text-encoding-for","title":"Efficient and Effective Text Encoding for Chinese LLaMA and Alpaca","date":"2023-04-17","arxiv_id":"2304.08177","n_code_links":6,"syntology":{"ran":18,"of":24,"n_ran_checked":9,"n_instrument":9,"unverified":6,"pointer_only":2,"phrase":"18 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 1 honoured, 0 violated, 8 with no contract checked; 9 where Syntology's instrument failed) · 6 unverified","official":{"repos":["ymcui/chinese-llama-alpaca","ymcui/chinese-llama-alpaca-2"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["listed","official","unlocated"]}}},{"paper":null,"slug":"hyper-decision-transformer-for-efficient","title":"Hyper-Decision Transformer for Efficient Online Policy Adaptation","date":"2023-04-17","arxiv_id":"2304.08487","n_code_links":0,"syntology":null},{"paper":"/paper/learning-to-compress-prompts-with-gist-tokens","slug":"learning-to-compress-prompts-with-gist-tokens","title":"Learning to Compress Prompts with Gist Tokens","date":"2023-04-17","arxiv_id":"2304.08467","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":["jayelm/gisting"],"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/long-term-forecasting-with-tide-time-series","slug":"long-term-forecasting-with-tide-time-series","title":"Long-term Forecasting with TiDE: Time-series Dense Encoder","date":"2023-04-17","arxiv_id":"2304.08424","n_code_links":5,"syntology":{"ran":2,"of":3,"n_ran_checked":2,"n_instrument":0,"unverified":1,"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) · 1 unverified","official":{"repos":["WenjieDu/PyPOTS"],"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/ptc-net-point-wise-transformer-with-sparse","slug":"ptc-net-point-wise-transformer-with-sparse","title":"PTC-Net: Point-Wise Transformer with Sparse Convolution Network for Place Recognition","date":"2023-04-17","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/strap-structured-object-affordance","slug":"strap-structured-object-affordance","title":"STRAP: Structured Object Affordance Segmentation with Point Supervision","date":"2023-04-17","arxiv_id":"2304.08492","n_code_links":1,"syntology":null},{"paper":null,"slug":"synthetic-data-from-diffusion-models-improves","title":"Synthetic Data from Diffusion Models Improves ImageNet Classification","date":"2023-04-17","arxiv_id":"2304.08466","n_code_links":0,"syntology":null},{"paper":"/paper/the-minipile-challenge-for-data-efficient","slug":"the-minipile-challenge-for-data-efficient","title":"The MiniPile Challenge for Data-Efficient Language Models","date":"2023-04-17","arxiv_id":"2304.08442","n_code_links":1,"syntology":null},{"paper":null,"slug":"transformer-with-selective-shuffled-position","title":"Transformer with Selective Shuffled Position Embedding and Key-Patch Exchange Strategy for Early Detection of Knee Osteoarthritis","date":"2023-04-17","arxiv_id":"2304.08364","n_code_links":0,"syntology":null},{"paper":null,"slug":"veco-2-0-cross-lingual-language-model-pre","title":"VECO 2.0: Cross-lingual Language Model Pre-training with Multi-granularity Contrastive Learning","date":"2023-04-17","arxiv_id":"2304.08205","n_code_links":0,"syntology":null},{"paper":"/paper/viplo-vision-transformer-based-pose","slug":"viplo-vision-transformer-based-pose","title":"ViPLO: Vision Transformer based Pose-Conditioned Self-Loop Graph for Human-Object Interaction Detection","date":"2023-04-17","arxiv_id":"2304.08114","n_code_links":1,"syntology":null},{"paper":"/paper/visual-instruction-tuning-1","slug":"visual-instruction-tuning-1","title":"Visual Instruction Tuning","date":"2023-04-17","arxiv_id":"2304.08485","n_code_links":13,"syntology":{"ran":16,"of":51,"n_ran_checked":8,"n_instrument":8,"unverified":35,"pointer_only":0,"phrase":"16 ran (of which 6 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 1 violated, 7 with no contract checked; 8 where Syntology's instrument failed) · 35 unverified","official":{"repos":["haotian-liu/LLaVA"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":8,"ran_from_kinds":["community","listed","named_in_paper","official"]}}},{"paper":"/paper/cat-nerf-constancy-aware-tx-2-former-for","slug":"cat-nerf-constancy-aware-tx-2-former-for","title":"CAT-NeRF: Constancy-Aware Tx$^2$Former for Dynamic Body Modeling","date":"2023-04-16","arxiv_id":"2304.07915","n_code_links":1,"syntology":null},{"paper":null,"slug":"obstacle-transformer-a-trajectory-prediction","title":"Obstacle-Transformer: A Trajectory Prediction Network Based on Surrounding Trajectories","date":"2023-04-16","arxiv_id":"2304.07711","n_code_links":0,"syntology":null},{"paper":"/paper/transfusionodom-interpretable-transformer","slug":"transfusionodom-interpretable-transformer","title":"TransFusionOdom: Interpretable Transformer-based LiDAR-Inertial Fusion Odometry Estimation","date":"2023-04-16","arxiv_id":"2304.07728","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-ctc-alignment-based-non-autoregressive","title":"A CTC Alignment-based Non-autoregressive Transformer for End-to-end Automatic Speech Recognition","date":"2023-04-15","arxiv_id":"2304.07611","n_code_links":0,"syntology":null},{"paper":"/paper/align-detr-improving-detr-with-simple-iou","slug":"align-detr-improving-detr-with-simple-iou","title":"Align-DETR: Enhancing End-to-end Object Detection with Aligned Loss","date":"2023-04-15","arxiv_id":"2304.07527","n_code_links":1,"syntology":{"ran":3,"of":3,"n_ran_checked":3,"n_instrument":0,"unverified":0,"pointer_only":0,"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) · 0 unverified","official":{"repos":["felixcaae/aligndetr"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"ma-vit-modality-agnostic-vision-transformers","title":"MA-ViT: Modality-Agnostic Vision Transformers for Face Anti-Spoofing","date":"2023-04-15","arxiv_id":"2304.07549","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-unified-hdr-imaging-method-with-pixel-and","title":"A Unified HDR Imaging Method with Pixel and Patch Level","date":"2023-04-14","arxiv_id":"2304.06943","n_code_links":0,"syntology":null},{"paper":"/paper/api-bank-a-benchmark-for-tool-augmented-llms","slug":"api-bank-a-benchmark-for-tool-augmented-llms","title":"API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMs","date":"2023-04-14","arxiv_id":"2304.08244","n_code_links":2,"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":null}},{"paper":"/paper/cad-rads-scoring-of-coronary-ct-angiography","slug":"cad-rads-scoring-of-coronary-ct-angiography","title":"CAD-RADS scoring of coronary CT angiography with Multi-Axis Vision Transformer: a clinically-inspired deep learning pipeline","date":"2023-04-14","arxiv_id":"2304.07277","n_code_links":1,"syntology":null},{"paper":null,"slug":"chatgpt-applications-opportunities-and","title":"ChatGPT: Applications, Opportunities, and Threats","date":"2023-04-14","arxiv_id":"2304.09103","n_code_links":0,"syntology":null},{"paper":null,"slug":"detr-with-additional-global-aggregation-for","title":"DETR with Additional Global Aggregation for Cross-domain Weakly Supervised Object Detection","date":"2023-04-14","arxiv_id":"2304.07082","n_code_links":0,"syntology":null},{"paper":"/paper/simplex-a-lexical-text-simplification","slug":"simplex-a-lexical-text-simplification","title":"SimpLex: a lexical text simplification architecture","date":"2023-04-14","arxiv_id":"2304.07002","n_code_links":1,"syntology":null},{"paper":"/paper/uncovering-the-inner-workings-of-stego-for","slug":"uncovering-the-inner-workings-of-stego-for","title":"Uncovering the Inner Workings of STEGO for Safe Unsupervised Semantic Segmentation","date":"2023-04-14","arxiv_id":"2304.07314","n_code_links":1,"syntology":null},{"paper":"/paper/agieval-a-human-centric-benchmark-for","slug":"agieval-a-human-centric-benchmark-for","title":"AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models","date":"2023-04-13","arxiv_id":"2304.06364","n_code_links":3,"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":["ruixiangcui/agieval"],"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/ddt-dual-branch-deformable-transformer-for","slug":"ddt-dual-branch-deformable-transformer-for","title":"DDT: Dual-branch Deformable Transformer for Image Denoising","date":"2023-04-13","arxiv_id":"2304.06346","n_code_links":1,"syntology":null},{"paper":"/paper/dynamic-mobile-former-strengthening-dynamic","slug":"dynamic-mobile-former-strengthening-dynamic","title":"Dynamic Mobile-Former: Strengthening Dynamic Convolution with Attention and Residual Connection in Kernel Space","date":"2023-04-13","arxiv_id":"2304.07254","n_code_links":1,"syntology":null},{"paper":null,"slug":"dynamite-dynamic-query-bootstrapping-for","title":"DynaMITe: Dynamic Query Bootstrapping for Multi-object Interactive Segmentation Transformer","date":"2023-04-13","arxiv_id":"2304.06668","n_code_links":0,"syntology":null},{"paper":null,"slug":"ewt-efficient-wavelet-transformer-for-single","title":"EWT: Efficient Wavelet-Transformer for Single Image Denoising","date":"2023-04-13","arxiv_id":"2304.06274","n_code_links":0,"syntology":null},{"paper":"/paper/modeling-dense-multimodal-interactions","slug":"modeling-dense-multimodal-interactions","title":"Modeling Dense Multimodal Interactions Between Biological Pathways and Histology for Survival Prediction","date":"2023-04-13","arxiv_id":"2304.06819","n_code_links":2,"syntology":{"ran":2,"of":2,"n_ran_checked":1,"n_instrument":1,"unverified":0,"pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["ajv012/survpath","mahmoodlab/survpath"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"rsir-transformer-hierarchical-vision","title":"RSIR Transformer: Hierarchical Vision Transformer using Random Sampling Windows and Important Region Windows","date":"2023-04-13","arxiv_id":"2304.06250","n_code_links":0,"syntology":null},{"paper":"/paper/sign-language-translation-from-instructional","slug":"sign-language-translation-from-instructional","title":"Sign Language Translation from Instructional Videos","date":"2023-04-13","arxiv_id":"2304.06371","n_code_links":1,"syntology":null},{"paper":"/paper/transhp-image-classification-with","slug":"transhp-image-classification-with","title":"TransHP: Image Classification with Hierarchical Prompting","date":"2023-04-13","arxiv_id":"2304.06385","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 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) · 0 unverified; the one sample that ran constructed an object rather than computing a result","official":{"repos":["wangwenhao0716/transhp"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/vision-diffmask-faithful-interpretation-of","slug":"vision-diffmask-faithful-interpretation-of","title":"VISION DIFFMASK: Faithful Interpretation of Vision Transformers with Differentiable Patch Masking","date":"2023-04-13","arxiv_id":"2304.06391","n_code_links":1,"syntology":null},{"paper":null,"slug":"distilling-token-pruned-pose-transformer-for","title":"Distilling Token-Pruned Pose Transformer for 2D Human Pose Estimation","date":"2023-04-12","arxiv_id":"2304.05548","n_code_links":0,"syntology":null},{"paper":null,"slug":"duformer-a-novel-architecture-for-power-line","title":"DUFormer: Solving Power Line Detection Task in Aerial Images using Semantic Segmentation","date":"2023-04-12","arxiv_id":"2304.05821","n_code_links":0,"syntology":null},{"paper":null,"slug":"galactic-chitchat-using-large-language-models","title":"Galactic ChitChat: Using Large Language Models to Converse with Astronomy Literature","date":"2023-04-12","arxiv_id":"2304.05406","n_code_links":0,"syntology":null},{"paper":null,"slug":"med-vt-multiscale-encoder-decoder-video","title":"MED-VT++: Unifying Multimodal Learning with a Multiscale Encoder-Decoder Video Transformer","date":"2023-04-12","arxiv_id":"2304.05930","n_code_links":0,"syntology":null},{"paper":null,"slug":"multi-scale-geometry-aware-transformer-for-3d","title":"Multi-scale Geometry-aware Transformer for 3D Point Cloud Classification","date":"2023-04-12","arxiv_id":"2304.05694","n_code_links":0,"syntology":null},{"paper":"/paper/patmat-person-aware-tuning-of-mask-aware","slug":"patmat-person-aware-tuning-of-mask-aware","title":"PATMAT: Person Aware Tuning of Mask-Aware Transformer for Face Inpainting","date":"2023-04-12","arxiv_id":"2304.06107","n_code_links":2,"syntology":null},{"paper":"/paper/real-time-trajectory-based-social-group","slug":"real-time-trajectory-based-social-group","title":"Real-time Trajectory-based Social Group Detection","date":"2023-04-12","arxiv_id":"2304.05678","n_code_links":1,"syntology":null},{"paper":"/paper/towards-evaluating-explanations-of-vision","slug":"towards-evaluating-explanations-of-vision","title":"Towards Evaluating Explanations of Vision Transformers for Medical Imaging","date":"2023-04-12","arxiv_id":"2304.06133","n_code_links":1,"syntology":null},{"paper":null,"slug":"chatipcc-grounding-conversational-ai-in","title":"chatClimate: Grounding Conversational AI in Climate Science","date":"2023-04-11","arxiv_id":"2304.05510","n_code_links":0,"syntology":null},{"paper":"/paper/chemcrow-augmenting-large-language-models","slug":"chemcrow-augmenting-large-language-models","title":"ChemCrow: Augmenting large-language models with chemistry tools","date":"2023-04-11","arxiv_id":"2304.05376","n_code_links":3,"syntology":{"ran":2,"of":3,"n_ran_checked":2,"n_instrument":0,"unverified":1,"pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 1 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","official":{"repos":["ur-whitelab/chemcrow-public","ur-whitelab/chemcrow-runs","whitead/synspace"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/data-efficient-image-quality-assessment-with","slug":"data-efficient-image-quality-assessment-with","title":"Data-Efficient Image Quality Assessment with Attention-Panel Decoder","date":"2023-04-11","arxiv_id":"2304.04952","n_code_links":1,"syntology":{"ran":2,"of":5,"n_ran_checked":2,"n_instrument":0,"unverified":3,"pointer_only":5,"phrase":"2 ran (of which 1 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) · 3 unverified","official":{"repos":["narthchin/deiqt"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":1,"n_ran_no_instrument_failure":2,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"distinguishing-chatgpt-3-5-4-generated-and","title":"Distinguishing ChatGPT(-3.5, -4)-generated and human-written papers through Japanese stylometric analysis","date":"2023-04-11","arxiv_id":"2304.05534","n_code_links":0,"syntology":null},{"paper":null,"slug":"mc-vivit-multi-branch-classifier-vivit-to","title":"MC-ViViT: Multi-branch Classifier-ViViT to detect Mild Cognitive Impairment in older adults using facial videos","date":"2023-04-11","arxiv_id":"2304.05292","n_code_links":0,"syntology":null},{"paper":"/paper/multi-graph-convolution-network-for-pose","slug":"multi-graph-convolution-network-for-pose","title":"Multi-Graph Convolution Network for Pose Forecasting","date":"2023-04-11","arxiv_id":"2304.04956","n_code_links":0,"syntology":null},{"paper":null,"slug":"sim-t-simplify-the-transformer-network-by","title":"Sim-T: Simplify the Transformer Network by Multiplexing Technique for Speech Recognition","date":"2023-04-11","arxiv_id":"2304.04991","n_code_links":0,"syntology":null},{"paper":null,"slug":"video-event-restoration-based-on-keyframes","title":"Video Event Restoration Based on Keyframes for Video Anomaly Detection","date":"2023-04-11","arxiv_id":"2304.05112","n_code_links":0,"syntology":null},{"paper":"/paper/detection-transformer-with-stable-matching","slug":"detection-transformer-with-stable-matching","title":"Detection Transformer with Stable Matching","date":"2023-04-10","arxiv_id":"2304.04742","n_code_links":2,"syntology":{"ran":7,"of":9,"n_ran_checked":4,"n_instrument":3,"unverified":2,"pointer_only":1,"phrase":"7 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; 3 where Syntology's instrument failed) · 2 unverified","official":{"repos":["idea-research/stable-dino"],"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":["found_in_text","official"]}}},{"paper":null,"slug":"feature-representation-learning-with-adaptive","title":"Feature Representation Learning with Adaptive Displacement Generation and Transformer Fusion for Micro-Expression Recognition","date":"2023-04-10","arxiv_id":"2304.04420","n_code_links":0,"syntology":null},{"paper":null,"slug":"high-dynamic-range-imaging-with-context-aware","title":"High Dynamic Range Imaging with Context-aware Transformer","date":"2023-04-10","arxiv_id":"2304.04416","n_code_links":0,"syntology":null},{"paper":null,"slug":"hst-mrf-heterogeneous-swin-transformer-with","title":"HST-MRF: Heterogeneous Swin Transformer with Multi-Receptive Field for Medical Image Segmentation","date":"2023-04-10","arxiv_id":"2304.04614","n_code_links":0,"syntology":null},{"paper":"/paper/multilingual-machine-translation-with-large","slug":"multilingual-machine-translation-with-large","title":"Multilingual Machine Translation with Large Language Models: Empirical Results and Analysis","date":"2023-04-10","arxiv_id":"2304.04675","n_code_links":2,"syntology":null},{"paper":null,"slug":"two-steps-forward-and-one-behind-rethinking","title":"Two Steps Forward and One Behind: Rethinking Time Series Forecasting with Deep Learning","date":"2023-04-10","arxiv_id":"2304.04553","n_code_links":0,"syntology":null},{"paper":"/paper/use-the-detection-transformer-as-a-data","slug":"use-the-detection-transformer-as-a-data","title":"Use the Detection Transformer as a Data Augmenter","date":"2023-04-10","arxiv_id":"2304.04554","n_code_links":1,"syntology":null},{"paper":"/paper/are-large-language-models-ready-for","slug":"are-large-language-models-ready-for","title":"Are Large Language Models Ready for Healthcare? A Comparative Study on Clinical Language Understanding","date":"2023-04-09","arxiv_id":"2304.05368","n_code_links":1,"syntology":null},{"paper":"/paper/slide-transformer-hierarchical-vision","slug":"slide-transformer-hierarchical-vision","title":"Slide-Transformer: Hierarchical Vision Transformer with Local Self-Attention","date":"2023-04-09","arxiv_id":"2304.04237","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 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) · 0 unverified; the one sample that ran constructed an object rather than computing a result","official":{"repos":["leaplabthu/slide-transformer"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"sparse-dense-fusion-for-3d-object-detection","title":"Sparse Dense Fusion for 3D Object Detection","date":"2023-04-09","arxiv_id":"2304.04179","n_code_links":0,"syntology":null},{"paper":null,"slug":"transformer-utilization-in-medical-image","title":"Transformer Utilization in Medical Image Segmentation Networks","date":"2023-04-09","arxiv_id":"2304.04225","n_code_links":0,"syntology":null},{"paper":"/paper/factify-2-a-multimodal-fake-news-and-satire","slug":"factify-2-a-multimodal-fake-news-and-satire","title":"Factify 2: A Multimodal Fake News and Satire News Dataset","date":"2023-04-08","arxiv_id":"2304.03897","n_code_links":1,"syntology":null},{"paper":null,"slug":"surrogate-lagrangian-relaxation-a-path-to","title":"Surrogate Lagrangian Relaxation: A Path To Retrain-free Deep Neural Network Pruning","date":"2023-04-08","arxiv_id":"2304.04120","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-cross-scale-hierarchical-transformer-with","title":"A Cross-Scale Hierarchical Transformer with Correspondence-Augmented Attention for inferring Bird's-Eye-View Semantic Segmentation","date":"2023-04-07","arxiv_id":"2304.03650","n_code_links":0,"syntology":null},{"paper":null,"slug":"cleansing-jewel-a-neural-spelling-correction","title":"Cleansing Jewel: A Neural Spelling Correction Model Built On Google OCR-ed Tibetan Manuscripts","date":"2023-04-07","arxiv_id":"2304.03427","n_code_links":0,"syntology":null},{"paper":"/paper/evaluating-the-logical-reasoning-ability-of","slug":"evaluating-the-logical-reasoning-ability-of","title":"Evaluating the Logical Reasoning Ability of ChatGPT and GPT-4","date":"2023-04-07","arxiv_id":"2304.03439","n_code_links":1,"syntology":null},{"paper":null,"slug":"pslt-a-light-weight-vision-transformer-with","title":"PSLT: A Light-weight Vision Transformer with Ladder Self-Attention and Progressive Shift","date":"2023-04-07","arxiv_id":"2304.03481","n_code_links":0,"syntology":null},{"paper":"/paper/sparseformer-sparse-visual-recognition-via","slug":"sparseformer-sparse-visual-recognition-via","title":"SparseFormer: Sparse Visual Recognition via Limited Latent Tokens","date":"2023-04-07","arxiv_id":"2304.03768","n_code_links":1,"syntology":null},{"paper":"/paper/all-keypoints-you-need-detecting-arbitrary","slug":"all-keypoints-you-need-detecting-arbitrary","title":"All Keypoints You Need: Detecting Arbitrary Keypoints on the Body of Triple, High, and Long Jump Athletes","date":"2023-04-06","arxiv_id":"2304.02939","n_code_links":1,"syntology":null},{"paper":null,"slug":"can-large-language-models-play-text-games","title":"Can Large Language Models Play Text Games Well? Current State-of-the-Art and Open Questions","date":"2023-04-06","arxiv_id":"2304.02868","n_code_links":0,"syntology":null},{"paper":null,"slug":"chatgpt-crawler-find-out-if-chatgpt-really","title":"ChatGPT-Crawler: Find out if ChatGPT really knows what it's talking about","date":"2023-04-06","arxiv_id":"2304.03325","n_code_links":0,"syntology":null},{"paper":null,"slug":"continual-detection-transformer-for","title":"Continual Detection Transformer for Incremental Object Detection","date":"2023-04-06","arxiv_id":"2304.03110","n_code_links":0,"syntology":null}],"record_sha256":"0c48ca7c9b1ffb076e02e5d8db99c8e8e0d1507b56cf7674cd6fe88291214a38","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}