{"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/residual-connection/papers/143","list_of":"/method/residual-connection","method":"Residual Connection","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":143,"pages_in_order":285,"rows_per_page":100,"rows":[14201,14300],"of":28401,"counts":{"archive_papers_tagged":28401,"with_a_code_link":12847,"where_syntology_ran_a_sample":3897,"not_listed_spam_title":0,"listed":28401,"listed_where_code_ran":3897,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":3291,"every_run_a_failure_of_syntologys_instrument":606,"listed_with_a_run_with_no_instrument_failure":3291,"listed_every_run_a_failure_of_syntologys_instrument":606,"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/residual-connection","prev":"/method/residual-connection/papers/142","next":"/method/residual-connection/papers/144","papers":[{"paper":"/paper/causal-reasoning-and-large-language-models","slug":"causal-reasoning-and-large-language-models","title":"Causal Reasoning and Large Language Models: Opening a New Frontier for Causality","date":"2023-04-28","arxiv_id":"2305.00050","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"1 ran (of which 0 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","official":{"repos":["py-why/pywhy-llm"],"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":null,"slug":"dd-cisenet-dual-domain-cross-iteration","title":"DD-CISENet: Dual-Domain Cross-Iteration Squeeze and Excitation Network for Accelerated MRI Reconstruction","date":"2023-04-28","arxiv_id":"2305.00088","n_code_links":0,"syntology":null},{"paper":null,"slug":"deep-intellectual-property-a-survey","title":"Deep Intellectual Property Protection: A Survey","date":"2023-04-28","arxiv_id":"2304.14613","n_code_links":0,"syntology":null},{"paper":null,"slug":"diamant-dual-image-attention-map-encoders-for","title":"DIAMANT: Dual Image-Attention Map Encoders For Medical Image Segmentation","date":"2023-04-28","arxiv_id":"2304.14571","n_code_links":0,"syntology":null},{"paper":"/paper/flowtransformer-a-transformer-framework-for","slug":"flowtransformer-a-transformer-framework-for","title":"FlowTransformer: A Transformer Framework for Flow-based Network Intrusion Detection Systems","date":"2023-04-28","arxiv_id":"2304.14746","n_code_links":1,"syntology":null},{"paper":"/paper/llama-adapter-v2-parameter-efficient-visual","slug":"llama-adapter-v2-parameter-efficient-visual","title":"LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model","date":"2023-04-28","arxiv_id":"2304.15010","n_code_links":3,"syntology":{"ran":0,"of":1,"n_ran_checked":0,"n_instrument":0,"unverified":1,"pointer_only":1,"phrase":"0 ran · 1 unverified","official":{"repos":["zrrskywalker/llama-adapter"],"state":"official: not harvested","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":[]}}},{"paper":null,"slug":"mask-cnn-transformer-for-real-time-multi","title":"MASK-CNN-Transformer For Real-Time Multi-Label Weather Recognition","date":"2023-04-28","arxiv_id":"2304.14857","n_code_links":0,"syntology":null},{"paper":null,"slug":"mudiff-unified-diffusion-for-complete","title":"MUDiff: Unified Diffusion for Complete Molecule Generation","date":"2023-04-28","arxiv_id":"2304.14621","n_code_links":0,"syntology":null},{"paper":"/paper/residual-transformer-with-dual-residual","slug":"residual-transformer-with-dual-residual","title":"ResiDual: Transformer with Dual Residual Connections","date":"2023-04-28","arxiv_id":"2304.14802","n_code_links":1,"syntology":null},{"paper":"/paper/speak-memory-an-archaeology-of-books-known-to","slug":"speak-memory-an-archaeology-of-books-known-to","title":"Speak, Memory: An Archaeology of Books Known to ChatGPT/GPT-4","date":"2023-04-28","arxiv_id":"2305.00118","n_code_links":1,"syntology":{"ran":1,"of":2,"n_ran_checked":0,"n_instrument":1,"unverified":1,"pointer_only":2,"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) · 1 unverified","official":{"repos":["bamman-group/gpt4-books"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/towards-automated-circuit-discovery-for-1","slug":"towards-automated-circuit-discovery-for-1","title":"Towards Automated Circuit Discovery for Mechanistic Interpretability","date":"2023-04-28","arxiv_id":"2304.14997","n_code_links":4,"syntology":{"ran":2,"of":5,"n_ran_checked":2,"n_instrument":0,"unverified":3,"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) · 3 unverified","official":{"repos":["arthurconmy/automatic-circuit-discovery","neelnanda-io/transformerlens"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":"/paper/towards-better-domain-adaptation-for-self","slug":"towards-better-domain-adaptation-for-self","title":"Towards Better Domain Adaptation for Self-supervised Models: A Case Study of Child ASR","date":"2023-04-28","arxiv_id":"2305.00115","n_code_links":1,"syntology":null},{"paper":null,"slug":"assessing-text-mining-and-technical-analyses","title":"Assessing Text Mining and Technical Analyses on Forecasting Financial Time Series","date":"2023-04-27","arxiv_id":"2304.14544","n_code_links":0,"syntology":null},{"paper":"/paper/boosting-big-brother-attacking-search-engines","slug":"boosting-big-brother-attacking-search-engines","title":"Boosting Big Brother: Attacking Search Engines with Encodings","date":"2023-04-27","arxiv_id":"2304.14031","n_code_links":1,"syntology":null},{"paper":null,"slug":"chatgpt-as-an-attack-tool-stealthy-textual","title":"ChatGPT as an Attack Tool: Stealthy Textual Backdoor Attack via Blackbox Generative Model Trigger","date":"2023-04-27","arxiv_id":"2304.14475","n_code_links":0,"syntology":null},{"paper":null,"slug":"conscendi-a-contrastive-and-scenario-guided","title":"CONSCENDI: A Contrastive and Scenario-Guided Distillation Approach to Guardrail Models for Virtual Assistants","date":"2023-04-27","arxiv_id":"2304.14364","n_code_links":0,"syntology":null},{"paper":"/paper/datacomp-in-search-of-the-next-generation-of","slug":"datacomp-in-search-of-the-next-generation-of","title":"DataComp: In search of the next generation of multimodal datasets","date":"2023-04-27","arxiv_id":"2304.14108","n_code_links":3,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":1,"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":["mlfoundations/datacomp"],"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/deeply-coupled-convolution-transformer-with","slug":"deeply-coupled-convolution-transformer-with","title":"Deeply-Coupled Convolution-Transformer with Spatial-temporal Complementary Learning for Video-based Person Re-identification","date":"2023-04-27","arxiv_id":"2304.14122","n_code_links":1,"syntology":null},{"paper":null,"slug":"distinguishing-a-planetary-transit-from-false","title":"Distinguishing a planetary transit from false positives: a Transformer-based classification for planetary transit signals","date":"2023-04-27","arxiv_id":"2304.14283","n_code_links":0,"syntology":null},{"paper":"/paper/exploiting-inductive-bias-in-transformer-for","slug":"exploiting-inductive-bias-in-transformer-for","title":"Exploiting Inductive Bias in Transformer for Point Cloud Classification and Segmentation","date":"2023-04-27","arxiv_id":"2304.14124","n_code_links":1,"syntology":null},{"paper":null,"slug":"framing-the-news-from-human-perception-to","title":"Framing the News:From Human Perception to Large Language Model Inferences","date":"2023-04-27","arxiv_id":"2304.14456","n_code_links":0,"syntology":null},{"paper":"/paper/large-language-models-are-state-of-the-art-1","slug":"large-language-models-are-state-of-the-art-1","title":"ICE-Score: Instructing Large Language Models to Evaluate Code","date":"2023-04-27","arxiv_id":"2304.14317","n_code_links":2,"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: 2 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","official":{"repos":["terryyz/llm-code-eval","terryyz/ice-score"],"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/lightweight-pre-trained-transformers-for","slug":"lightweight-pre-trained-transformers-for","title":"Lightweight, Pre-trained Transformers for Remote Sensing Timeseries","date":"2023-04-27","arxiv_id":"2304.14065","n_code_links":1,"syntology":{"ran":7,"of":13,"n_ran_checked":7,"n_instrument":0,"unverified":6,"pointer_only":0,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 6 unverified","official":{"repos":["nasaharvest/presto"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":6,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"neural-keyphrase-generation-analysis-and-1","title":"Neural Keyphrase Generation: Analysis and Evaluation","date":"2023-04-27","arxiv_id":"2304.13883","n_code_links":0,"syntology":null},{"paper":"/paper/optimization-inspired-cross-attention","slug":"optimization-inspired-cross-attention","title":"Optimization-Inspired Cross-Attention Transformer for Compressive Sensing","date":"2023-04-27","arxiv_id":"2304.13986","n_code_links":1,"syntology":null},{"paper":null,"slug":"origin-tracing-and-detecting-of-llms","title":"Origin Tracing and Detecting of LLMs","date":"2023-04-27","arxiv_id":"2304.14072","n_code_links":0,"syntology":null},{"paper":"/paper/pybibx-a-python-library-for-bibliometric-and","slug":"pybibx-a-python-library-for-bibliometric-and","title":"pyBibX -- A Python Library for Bibliometric and Scientometric Analysis Powered with Artificial Intelligence Tools","date":"2023-04-27","arxiv_id":"2304.14516","n_code_links":1,"syntology":null},{"paper":"/paper/swectrl-mini-a-data-transparent-transformer","slug":"swectrl-mini-a-data-transparent-transformer","title":"SweCTRL-Mini: a data-transparent Transformer-based large language model for controllable text generation in Swedish","date":"2023-04-27","arxiv_id":"2304.13994","n_code_links":1,"syntology":null},{"paper":null,"slug":"tempee-temporal-spatial-parallel-transformer","title":"TempEE: Temporal-Spatial Parallel Transformer for Radar Echo Extrapolation Beyond Auto-Regression","date":"2023-04-27","arxiv_id":"2304.14131","n_code_links":0,"syntology":null},{"paper":"/paper/we-re-afraid-language-models-aren-t-modeling","slug":"we-re-afraid-language-models-aren-t-modeling","title":"We're Afraid Language Models Aren't Modeling Ambiguity","date":"2023-04-27","arxiv_id":"2304.14399","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-case-based-reasoning-framework-for-adaptive","title":"Prompting GPT-3.5 for Text-to-SQL with De-semanticization and Skeleton Retrieval","date":"2023-04-26","arxiv_id":"2304.13301","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-deep-image-retrieval-network-using-max-m","title":"A deep image retrieval network using Max-m-Min pooling and morphological feature generating residual blocks","date":"2023-04-26","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"evaluation-of-gpt-3-5-and-gpt-4-for","title":"Evaluation of GPT-3.5 and GPT-4 for supporting real-world information needs in healthcare delivery","date":"2023-04-26","arxiv_id":"2304.13714","n_code_links":0,"syntology":null},{"paper":null,"slug":"exploiting-cnns-for-semantic-segmentation","title":"Exploiting CNNs for Semantic Segmentation with Pascal VOC","date":"2023-04-26","arxiv_id":"2304.13216","n_code_links":0,"syntology":null},{"paper":"/paper/exploring-the-curious-case-of-code-prompts","slug":"exploring-the-curious-case-of-code-prompts","title":"Exploring the Curious Case of Code Prompts","date":"2023-04-26","arxiv_id":"2304.13250","n_code_links":1,"syntology":{"ran":2,"of":6,"n_ran_checked":2,"n_instrument":0,"unverified":4,"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) · 4 unverified","official":{"repos":["zharry29/codex_vs_gpt3"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":4,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"extracting-structured-seed-mediated-gold","title":"Extracting Structured Seed-Mediated Gold Nanorod Growth Procedures from Literature with GPT-3","date":"2023-04-26","arxiv_id":"2304.13846","n_code_links":0,"syntology":null},{"paper":null,"slug":"fine-tuning-with-abnormal-examples","title":"Fine Tuning with Abnormal Examples","date":"2023-04-26","arxiv_id":"2304.13783","n_code_links":0,"syntology":null},{"paper":"/paper/hausanlp-at-semeval-2023-task-12-leveraging","slug":"hausanlp-at-semeval-2023-task-12-leveraging","title":"HausaNLP at SemEval-2023 Task 12: Leveraging African Low Resource TweetData for Sentiment Analysis","date":"2023-04-26","arxiv_id":"2304.13634","n_code_links":1,"syntology":null},{"paper":"/paper/impact-of-position-bias-on-language-models-in","slug":"impact-of-position-bias-on-language-models-in","title":"Technical Report: Impact of Position Bias on Language Models in Token Classification","date":"2023-04-26","arxiv_id":"2304.13567","n_code_links":2,"syntology":null},{"paper":"/paper/is-a-prompt-and-a-few-samples-all-you-need","slug":"is-a-prompt-and-a-few-samples-all-you-need","title":"The Parrot Dilemma: Human-Labeled vs. LLM-augmented Data in Classification Tasks","date":"2023-04-26","arxiv_id":"2304.13861","n_code_links":2,"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":["andersgiovanni/worker_vs_gpt","AGMoller/worker_vs_gpt"],"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/scatterformer-locally-invariant-scattering","slug":"scatterformer-locally-invariant-scattering","title":"ScatterFormer: Locally-Invariant Scattering Transformer for Patient-Independent Multispectral Detection of Epileptiform Discharges","date":"2023-04-26","arxiv_id":"2304.14919","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":["albertcheng19/scatterformer"],"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":null,"slug":"sensitive-tuning-of-large-scale-cnns-for-e2e","title":"Training Large Scale Polynomial CNNs for E2E Inference over Homomorphic Encryption","date":"2023-04-26","arxiv_id":"2304.14836","n_code_links":0,"syntology":null},{"paper":"/paper/simara-a-database-for-key-value-information","slug":"simara-a-database-for-key-value-information","title":"SIMARA: a database for key-value information extraction from full pages","date":"2023-04-26","arxiv_id":"2304.13606","n_code_links":0,"syntology":null},{"paper":"/paper/stir-siamese-transformer-for-image-retrieval","slug":"stir-siamese-transformer-for-image-retrieval","title":"STIR: Siamese Transformer for Image Retrieval Postprocessing","date":"2023-04-26","arxiv_id":"2304.13393","n_code_links":1,"syntology":null},{"paper":"/paper/textdeformer-geometry-manipulation-using-text","slug":"textdeformer-geometry-manipulation-using-text","title":"TextDeformer: Geometry Manipulation using Text Guidance","date":"2023-04-26","arxiv_id":"2304.13348","n_code_links":1,"syntology":{"ran":11,"of":16,"n_ran_checked":10,"n_instrument":1,"unverified":5,"pointer_only":1,"phrase":"11 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 0 violated, 10 with no contract checked; 1 where Syntology's instrument failed) · 5 unverified","official":{"repos":["threedle/TextDeformer"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":5,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"the-closeness-of-in-context-learning-and","title":"The Closeness of In-Context Learning and Weight Shifting for Softmax Regression","date":"2023-04-26","arxiv_id":"2304.13276","n_code_links":0,"syntology":null},{"paper":null,"slug":"towards-multi-modal-dbmss-for-seamless","title":"Towards Multi-Modal DBMSs for Seamless Querying of Texts and Tables","date":"2023-04-26","arxiv_id":"2304.13559","n_code_links":0,"syntology":null},{"paper":"/paper/ai-assisted-coding-experiments-with-gpt-4","slug":"ai-assisted-coding-experiments-with-gpt-4","title":"AI-assisted coding: Experiments with GPT-4","date":"2023-04-25","arxiv_id":"2304.13187","n_code_links":1,"syntology":null},{"paper":null,"slug":"application-of-transformers-for-nonlinear","title":"Application of Transformers for Nonlinear Channel Compensation in Optical Systems","date":"2023-04-25","arxiv_id":"2304.13119","n_code_links":0,"syntology":null},{"paper":"/paper/completionformer-depth-completion-with","slug":"completionformer-depth-completion-with","title":"CompletionFormer: Depth Completion with Convolutions and Vision Transformers","date":"2023-04-25","arxiv_id":"2304.13030","n_code_links":1,"syntology":null},{"paper":null,"slug":"depth-relative-self-attention-for-monocular","title":"Depth-Relative Self Attention for Monocular Depth Estimation","date":"2023-04-25","arxiv_id":"2304.12849","n_code_links":0,"syntology":null},{"paper":"/paper/duett-dual-event-time-transformer-for","slug":"duett-dual-event-time-transformer-for","title":"DuETT: Dual Event Time Transformer for Electronic Health Records","date":"2023-04-25","arxiv_id":"2304.13017","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":1,"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":["layer6ai-labs/duett"],"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/escaping-the-sentence-level-paradigm-in","slug":"escaping-the-sentence-level-paradigm-in","title":"Escaping the sentence-level paradigm in machine translation","date":"2023-04-25","arxiv_id":"2304.12959","n_code_links":1,"syntology":null},{"paper":"/paper/imixer-hierarchical-hopfield-network-implies","slug":"imixer-hierarchical-hopfield-network-implies","title":"iMixer: hierarchical Hopfield network implies an invertible, implicit and iterative MLP-Mixer","date":"2023-04-25","arxiv_id":"2304.13061","n_code_links":1,"syntology":null},{"paper":"/paper/introducing-mbib-the-first-media-bias","slug":"introducing-mbib-the-first-media-bias","title":"Introducing MBIB -- the first Media Bias Identification Benchmark Task and Dataset Collection","date":"2023-04-25","arxiv_id":"2304.13148","n_code_links":1,"syntology":null},{"paper":null,"slug":"lemart-label-efficient-masked-region","title":"LEMaRT: Label-Efficient Masked Region Transform for Image Harmonization","date":"2023-04-25","arxiv_id":"2304.13166","n_code_links":0,"syntology":null},{"paper":"/paper/measuring-massive-multitask-chinese","slug":"measuring-massive-multitask-chinese","title":"Measuring Massive Multitask Chinese Understanding","date":"2023-04-25","arxiv_id":"2304.12986","n_code_links":2,"syntology":{"ran":3,"of":3,"n_ran_checked":0,"n_instrument":3,"unverified":0,"pointer_only":3,"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":["Felixgithub2017/MMCU"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official","unlocated"]}}},{"paper":null,"slug":"nlp-ltu-at-semeval-2023-task-10-the-impact-of","title":"NLP-LTU at SemEval-2023 Task 10: The Impact of Data Augmentation and Semi-Supervised Learning Techniques on Text Classification Performance on an Imbalanced Dataset","date":"2023-04-25","arxiv_id":"2304.12847","n_code_links":0,"syntology":null},{"paper":null,"slug":"objectives-matter-understanding-the-impact-of","title":"Objectives Matter: Understanding the Impact of Self-Supervised Objectives on Vision Transformer Representations","date":"2023-04-25","arxiv_id":"2304.13089","n_code_links":0,"syntology":null},{"paper":"/paper/sdsc-unet-dual-skip-connection-vit-based-u","slug":"sdsc-unet-dual-skip-connection-vit-based-u","title":"SDSC-UNet: Dual Skip Connection ViT-based U-shaped Model for Building Extraction","date":"2023-04-25","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"semantic-compression-with-large-language","title":"Semantic Compression With Large Language Models","date":"2023-04-25","arxiv_id":"2304.12512","n_code_links":0,"syntology":null},{"paper":null,"slug":"state-spaces-aren-t-enough-machine","title":"State Spaces Aren't Enough: Machine Translation Needs Attention","date":"2023-04-25","arxiv_id":"2304.12776","n_code_links":0,"syntology":null},{"paper":null,"slug":"stm-unet-an-efficient-u-shaped-architecture","title":"STM-UNet: An Efficient U-shaped Architecture Based on Swin Transformer and Multi-scale MLP for Medical Image Segmentation","date":"2023-04-25","arxiv_id":"2304.12615","n_code_links":0,"syntology":null},{"paper":null,"slug":"swinfsr-stereo-image-super-resolution-using","title":"SwinFSR: Stereo Image Super-Resolution using SwinIR and Frequency Domain Knowledge","date":"2023-04-25","arxiv_id":"2304.12556","n_code_links":0,"syntology":null},{"paper":null,"slug":"the-potential-of-visual-chatgpt-for-remote","title":"The Potential of Visual ChatGPT For Remote Sensing","date":"2023-04-25","arxiv_id":"2304.13009","n_code_links":0,"syntology":null},{"paper":null,"slug":"theory-of-posterior-concentration-for","title":"Theory of Posterior Concentration for Generalized Bayesian Additive Regression Trees","date":"2023-04-25","arxiv_id":"2304.12505","n_code_links":0,"syntology":null},{"paper":null,"slug":"what-does-bert-learn-about-prosody","title":"What does BERT learn about prosody?","date":"2023-04-25","arxiv_id":"2304.12706","n_code_links":0,"syntology":null},{"paper":null,"slug":"artificial-general-intelligence-agi-for","title":"AGI: Artificial General Intelligence for Education","date":"2023-04-24","arxiv_id":"2304.12479","n_code_links":0,"syntology":null},{"paper":null,"slug":"augmentation-based-domain-generalization-for","title":"Augmentation-based Domain Generalization for Semantic Segmentation","date":"2023-04-24","arxiv_id":"2304.12122","n_code_links":0,"syntology":null},{"paper":"/paper/better-question-answering-models-on-a-budget","slug":"better-question-answering-models-on-a-budget","title":"Better Question-Answering Models on a Budget","date":"2023-04-24","arxiv_id":"2304.12370","n_code_links":1,"syntology":null},{"paper":"/paper/directed-acyclic-transformer-pre-training-for","slug":"directed-acyclic-transformer-pre-training-for","title":"Directed Acyclic Transformer Pre-training for High-quality Non-autoregressive Text Generation","date":"2023-04-24","arxiv_id":"2304.11791","n_code_links":1,"syntology":{"ran":4,"of":4,"n_ran_checked":2,"n_instrument":2,"unverified":0,"pointer_only":4,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 1 honoured, 1 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["thu-coai/da-transformer"],"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","unlocated"]}}},{"paper":"/paper/explicit-correspondence-matching-for","slug":"explicit-correspondence-matching-for","title":"Explicit Correspondence Matching for Generalizable Neural Radiance Fields","date":"2023-04-24","arxiv_id":"2304.12294","n_code_links":1,"syntology":{"ran":8,"of":9,"n_ran_checked":8,"n_instrument":0,"unverified":1,"pointer_only":0,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","official":{"repos":["donydchen/matchnerf"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"extreme-classification-for-answer-type","title":"Extreme Classification for Answer Type Prediction in Question Answering","date":"2023-04-24","arxiv_id":"2304.12395","n_code_links":0,"syntology":null},{"paper":"/paper/generation-driven-contrastive-self-training","slug":"generation-driven-contrastive-self-training","title":"Generation-driven Contrastive Self-training for Zero-shot Text Classification with Instruction-following LLM","date":"2023-04-24","arxiv_id":"2304.11872","n_code_links":1,"syntology":null},{"paper":"/paper/irnext-rethinking-convolutional-network","slug":"irnext-rethinking-convolutional-network","title":"IRNeXt: Rethinking Convolutional Network Design for Image Restoration","date":"2023-04-24","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"master-meta-style-transformer-for","title":"Master: Meta Style Transformer for Controllable Zero-Shot and Few-Shot Artistic Style Transfer","date":"2023-04-24","arxiv_id":"2304.11818","n_code_links":0,"syntology":null},{"paper":"/paper/mixpro-data-augmentation-with-maskmix-and","slug":"mixpro-data-augmentation-with-maskmix-and","title":"MixPro: Data Augmentation with MaskMix and Progressive Attention Labeling for Vision Transformer","date":"2023-04-24","arxiv_id":"2304.12043","n_code_links":1,"syntology":{"ran":16,"of":18,"n_ran_checked":9,"n_instrument":7,"unverified":2,"pointer_only":8,"phrase":"16 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 0 violated, 9 with no contract checked; 7 where Syntology's instrument failed) · 2 unverified","official":{"repos":["fistyee/mixpro"],"state":"official (archive's flag): 16 ran","n_ran":16,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"noisetrans-point-cloud-denoising-with","title":"NoiseTrans: Point Cloud Denoising with Transformers","date":"2023-04-24","arxiv_id":"2304.11812","n_code_links":0,"syntology":null},{"paper":null,"slug":"now-you-see-me-robust-approach-to-partial","title":"Now You See Me: Robust approach to Partial Occlusions","date":"2023-04-24","arxiv_id":"2304.11779","n_code_links":0,"syntology":null},{"paper":"/paper/once-detected-never-lost-surpassing-human","slug":"once-detected-never-lost-surpassing-human","title":"Once Detected, Never Lost: Surpassing Human Performance in Offline LiDAR based 3D Object Detection","date":"2023-04-24","arxiv_id":"2304.12315","n_code_links":2,"syntology":{"ran":3,"of":5,"n_ran_checked":0,"n_instrument":3,"unverified":2,"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) · 2 unverified","official":{"repos":["tusen-ai/sst"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/paragraph2graph-a-gnn-based-framework-for","slug":"paragraph2graph-a-gnn-based-framework-for","title":"PARAGRAPH2GRAPH: A GNN-based framework for layout paragraph analysis","date":"2023-04-24","arxiv_id":"2304.11810","n_code_links":1,"syntology":null},{"paper":"/paper/pre-trained-embeddings-for-entity-resolution","slug":"pre-trained-embeddings-for-entity-resolution","title":"Pre-trained Embeddings for Entity Resolution: An Experimental Analysis [Experiment, Analysis & Benchmark]","date":"2023-04-24","arxiv_id":"2304.12329","n_code_links":1,"syntology":null},{"paper":"/paper/rank-flow-embedding-for-unsupervised-and-semi-1","slug":"rank-flow-embedding-for-unsupervised-and-semi-1","title":"Rank Flow Embedding for Unsupervised and Semi-Supervised Manifold Learning","date":"2023-04-24","arxiv_id":"2304.12448","n_code_links":1,"syntology":null},{"paper":"/paper/recurrent-transformer-encoders-for-vision","slug":"recurrent-transformer-encoders-for-vision","title":"Vision-based Estimation of Fatigue and Engagement in Cognitive Training Sessions","date":"2023-04-24","arxiv_id":"2304.12470","n_code_links":1,"syntology":null},{"paper":null,"slug":"self-regularised-minimum-latency-training-for","title":"Self-regularised Minimum Latency Training for Streaming Transformer-based Speech Recognition","date":"2023-04-24","arxiv_id":"2304.11985","n_code_links":0,"syntology":null},{"paper":"/paper/socialdial-a-benchmark-for-socially-aware","slug":"socialdial-a-benchmark-for-socially-aware","title":"SocialDial: A Benchmark for Socially-Aware Dialogue Systems","date":"2023-04-24","arxiv_id":"2304.12026","n_code_links":1,"syntology":null},{"paper":"/paper/text-to-audio-generation-using-instruction","slug":"text-to-audio-generation-using-instruction","title":"Text-to-Audio Generation using Instruction-Tuned LLM and Latent Diffusion Model","date":"2023-04-24","arxiv_id":"2304.13731","n_code_links":1,"syntology":null},{"paper":null,"slug":"transformer-based-stereo-aware-3d-object","title":"Transformer-based stereo-aware 3D object detection from binocular images","date":"2023-04-24","arxiv_id":"2304.11906","n_code_links":0,"syntology":null},{"paper":"/paper/universal-domain-adaptation-via-compressive","slug":"universal-domain-adaptation-via-compressive","title":"Universal Domain Adaptation via Compressive Attention Matching","date":"2023-04-24","arxiv_id":"2304.11862","n_code_links":0,"syntology":null},{"paper":"/paper/wizardlm-empowering-large-language-models-to","slug":"wizardlm-empowering-large-language-models-to","title":"WizardLM: Empowering Large Language Models to Follow Complex Instructions","date":"2023-04-24","arxiv_id":"2304.12244","n_code_links":4,"syntology":{"ran":2,"of":3,"n_ran_checked":1,"n_instrument":1,"unverified":1,"pointer_only":3,"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":["nlpxucan/wizardlm"],"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":["listed","official"]}}},{"paper":"/paper/exploring-challenges-of-deploying-bert-based","slug":"exploring-challenges-of-deploying-bert-based","title":"Processing Natural Language on Embedded Devices: How Well Do Transformer Models Perform?","date":"2023-04-23","arxiv_id":"2304.11520","n_code_links":2,"syntology":null},{"paper":null,"slug":"vision-transformer-for-efficient-chest-x-ray","title":"Vision Transformer for Efficient Chest X-ray and Gastrointestinal Image Classification","date":"2023-04-23","arxiv_id":"2304.11529","n_code_links":0,"syntology":null},{"paper":null,"slug":"bitrackgan-cascaded-cyclegans-to-constraint","title":"BiTrackGAN: Cascaded CycleGANs to Constraint Face Aging","date":"2023-04-22","arxiv_id":"2304.11313","n_code_links":0,"syntology":null},{"paper":"/paper/boosting-theory-of-mind-performance-in-large","slug":"boosting-theory-of-mind-performance-in-large","title":"Boosting Theory-of-Mind Performance in Large Language Models via Prompting","date":"2023-04-22","arxiv_id":"2304.11490","n_code_links":1,"syntology":null},{"paper":"/paper/dilated-unet-a-fast-and-accurate-medical","slug":"dilated-unet-a-fast-and-accurate-medical","title":"Dilated-UNet: A Fast and Accurate Medical Image Segmentation Approach using a Dilated Transformer and U-Net Architecture","date":"2023-04-22","arxiv_id":"2304.11450","n_code_links":1,"syntology":null},{"paper":null,"slug":"incomplete-multimodal-learning-for-remote","title":"Incomplete Multimodal Learning for Remote Sensing Data Fusion","date":"2023-04-22","arxiv_id":"2304.11381","n_code_links":0,"syntology":null},{"paper":null,"slug":"l3cube-indicsbert-a-simple-approach-for","title":"L3Cube-IndicSBERT: A simple approach for learning cross-lingual sentence representations using multilingual BERT","date":"2023-04-22","arxiv_id":"2304.11434","n_code_links":0,"syntology":null},{"paper":null,"slug":"vision-transformers-a-new-approach-for-high","title":"Vision Transformers, a new approach for high-resolution and large-scale mapping of canopy heights","date":"2023-04-22","arxiv_id":"2304.11487","n_code_links":0,"syntology":null},{"paper":"/paper/visithers-visible-thermal-infrared-stereo","slug":"visithers-visible-thermal-infrared-stereo","title":"VisiTherS: Visible-thermal infrared stereo disparity estimation of human silhouette","date":"2023-04-22","arxiv_id":"2304.11291","n_code_links":1,"syntology":null},{"paper":"/paper/a-group-specific-approach-to-nlp-for-hate","slug":"a-group-specific-approach-to-nlp-for-hate","title":"A Group-Specific Approach to NLP for Hate Speech Detection","date":"2023-04-21","arxiv_id":"2304.11223","n_code_links":1,"syntology":null}],"record_sha256":"32b8cbcc07c1bf07ebbddd161567ba7f24a2d69cffe757c843e7cc6be71a4d2f","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}