{"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/attention/papers/95","list_of":"/method/attention","method":"Attention","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":95,"pages_in_order":316,"rows_per_page":100,"rows":[9401,9500],"of":31583,"counts":{"archive_papers_tagged":31583,"with_a_code_link":13473,"where_syntology_ran_a_sample":3998,"not_listed_spam_title":0,"listed":31583,"listed_where_code_ran":3998,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":3366,"every_run_a_failure_of_syntologys_instrument":632,"listed_with_a_run_with_no_instrument_failure":3366,"listed_every_run_a_failure_of_syntologys_instrument":632,"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/attention","prev":"/method/attention/papers/94","next":"/method/attention/papers/96","papers":[{"paper":null,"slug":"the-lou-dataset-exploring-the-impact-of","title":"The Lou Dataset -- Exploring the Impact of Gender-Fair Language in German Text Classification","date":"2024-09-26","arxiv_id":"2409.17929","n_code_links":0,"syntology":null},{"paper":null,"slug":"towards-the-mitigation-of-confirmation-bias","title":"Towards the Mitigation of Confirmation Bias in Semi-supervised Learning: a Debiased Training Perspective","date":"2024-09-26","arxiv_id":"2409.18316","n_code_links":0,"syntology":null},{"paper":"/paper/trustworthy-text-to-image-diffusion-models-a","slug":"trustworthy-text-to-image-diffusion-models-a","title":"Trustworthy Text-to-Image Diffusion Models: A Timely and Focused Survey","date":"2024-09-26","arxiv_id":"2409.18214","n_code_links":1,"syntology":null},{"paper":"/paper/unifying-dimensions-a-linear-adaptive","slug":"unifying-dimensions-a-linear-adaptive","title":"Unifying Dimensions: A Linear Adaptive Approach to Lightweight Image Super-Resolution","date":"2024-09-26","arxiv_id":"2409.17597","n_code_links":1,"syntology":null},{"paper":null,"slug":"unsupervised-learning-based-multi-scale","title":"Unsupervised Learning Based Multi-Scale Exposure Fusion","date":"2024-09-26","arxiv_id":"2409.17830","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-prompting-based-representation-learning","title":"A Prompting-Based Representation Learning Method for Recommendation with Large Language Models","date":"2024-09-25","arxiv_id":"2409.16674","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-roadmap-for-embodied-and-social-grounding","title":"A Roadmap for Embodied and Social Grounding in LLMs","date":"2024-09-25","arxiv_id":"2409.16900","n_code_links":0,"syntology":null},{"paper":null,"slug":"accelerating-multi-block-constrained","title":"Accelerating Multi-Block Constrained Optimization Through Learning to Optimize","date":"2024-09-25","arxiv_id":"2409.17320","n_code_links":0,"syntology":null},{"paper":null,"slug":"agregnet-a-deep-regression-network-for-flower","title":"AgRegNet: A Deep Regression Network for Flower and Fruit Density Estimation, Localization, and Counting in Orchards","date":"2024-09-25","arxiv_id":"2409.17400","n_code_links":0,"syntology":null},{"paper":"/paper/alignedkv-reducing-memory-access-of-kv-cache","slug":"alignedkv-reducing-memory-access-of-kv-cache","title":"AlignedKV: Reducing Memory Access of KV-Cache with Precision-Aligned Quantization","date":"2024-09-25","arxiv_id":"2409.16546","n_code_links":1,"syntology":null},{"paper":null,"slug":"an-integrated-deep-learning-framework-for","title":"Targeted Neural Architectures in Multi-Objective Frameworks for Complete Glioma Characterization from Multimodal MRI","date":"2024-09-25","arxiv_id":"2409.17273","n_code_links":0,"syntology":null},{"paper":"/paper/attention-prompting-on-image-for-large-vision","slug":"attention-prompting-on-image-for-large-vision","title":"Attention Prompting on Image for Large Vision-Language Models","date":"2024-09-25","arxiv_id":"2409.17143","n_code_links":1,"syntology":{"ran":8,"of":12,"n_ran_checked":5,"n_instrument":3,"unverified":4,"pointer_only":2,"phrase":"8 ran (of which 3 constructed an object rather than computing a result; 5 with no instrument failure: 2 honoured, 0 violated, 3 with no contract checked; 3 where Syntology's instrument failed) · 4 unverified","official":{"repos":["yu-rp/apiprompting"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":3,"n_ran_no_instrument_failure":5,"n_unverified":4,"ran_from_kinds":["official","unlocated"]}}},{"paper":null,"slug":"beyond-turing-test-can-gpt-4-sway-experts","title":"Beyond Turing Test: Can GPT-4 Sway Experts' Decisions?","date":"2024-09-25","arxiv_id":"2409.16710","n_code_links":0,"syntology":null},{"paper":null,"slug":"block-expanded-dinoret-adapting-natural","title":"Block Expanded DINORET: Adapting Natural Domain Foundation Models for Retinal Imaging Without Catastrophic Forgetting","date":"2024-09-25","arxiv_id":"2409.17332","n_code_links":0,"syntology":null},{"paper":"/paper/codeinsight-a-curated-dataset-of-practical","slug":"codeinsight-a-curated-dataset-of-practical","title":"CodeInsight: A Curated Dataset of Practical Coding Solutions from Stack Overflow","date":"2024-09-25","arxiv_id":"2409.16819","n_code_links":1,"syntology":null},{"paper":null,"slug":"deep-learning-and-machine-learning-advancing","title":"Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Handy Appetizer","date":"2024-09-25","arxiv_id":"2409.17120","n_code_links":0,"syntology":null},{"paper":"/paper/discovering-the-gems-in-early-layers","slug":"discovering-the-gems-in-early-layers","title":"Discovering the Gems in Early Layers: Accelerating Long-Context LLMs with 1000x Input Token Reduction","date":"2024-09-25","arxiv_id":"2409.17422","n_code_links":1,"syntology":{"ran":13,"of":13,"n_ran_checked":11,"n_instrument":2,"unverified":0,"pointer_only":3,"phrase":"13 ran (of which 0 constructed an object rather than computing a result; 11 with no instrument failure: 1 honoured, 1 violated, 9 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["salesforceairesearch/gemfilter"],"state":"official (archive's flag): 13 ran","n_ran":13,"n_constructed":0,"n_ran_no_instrument_failure":11,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"enhancing-automatic-keyphrase-labelling-with","title":"Enhancing Automatic Keyphrase Labelling with Text-to-Text Transfer Transformer (T5) Architecture: A Framework for Keyphrase Generation and Filtering","date":"2024-09-25","arxiv_id":"2409.16760","n_code_links":0,"syntology":null},{"paper":null,"slug":"enhancing-feature-selection-and","title":"Enhancing Feature Selection and Interpretability in AI Regression Tasks Through Feature Attribution","date":"2024-09-25","arxiv_id":"2409.16787","n_code_links":0,"syntology":null},{"paper":null,"slug":"event-triggered-non-linear-control-of","title":"Event-Triggered Non-Linear Control of Offshore MMC Grids for Asymmetrical AC Faults","date":"2024-09-25","arxiv_id":"2409.16743","n_code_links":0,"syntology":null},{"paper":null,"slug":"going-beyond-u-net-assessing-vision","title":"Going Beyond U-Net: Assessing Vision Transformers for Semantic Segmentation in Microscopy Image Analysis","date":"2024-09-25","arxiv_id":"2409.16940","n_code_links":0,"syntology":null},{"paper":"/paper/gradient-boosting-decision-trees-on-medical","slug":"gradient-boosting-decision-trees-on-medical","title":"Gradient Boosting Decision Trees on Medical Diagnosis over Tabular Data","date":"2024-09-25","arxiv_id":"2410.03705","n_code_links":1,"syntology":null},{"paper":null,"slug":"harnessing-diversity-for-important-data","title":"Harnessing Diversity for Important Data Selection in Pretraining Large Language Models","date":"2024-09-25","arxiv_id":"2409.16986","n_code_links":0,"syntology":null},{"paper":"/paper/hvt-a-comprehensive-vision-framework-for","slug":"hvt-a-comprehensive-vision-framework-for","title":"HVT: A Comprehensive Vision Framework for Learning in Non-Euclidean Space","date":"2024-09-25","arxiv_id":"2409.16897","n_code_links":1,"syntology":null},{"paper":"/paper/int-flashattention-enabling-flash-attention","slug":"int-flashattention-enabling-flash-attention","title":"INT-FlashAttention: Enabling Flash Attention for INT8 Quantization","date":"2024-09-25","arxiv_id":"2409.16997","n_code_links":1,"syntology":null},{"paper":"/paper/investigating-ocr-sensitive-neurons-to","slug":"investigating-ocr-sensitive-neurons-to","title":"Investigating OCR-Sensitive Neurons to Improve Entity Recognition in Historical Documents","date":"2024-09-25","arxiv_id":"2409.16934","n_code_links":1,"syntology":null},{"paper":null,"slug":"llama-sciq-an-educational-chatbot-for","title":"LLaMa-SciQ: An Educational Chatbot for Answering Science MCQ","date":"2024-09-25","arxiv_id":"2409.16779","n_code_links":0,"syntology":null},{"paper":null,"slug":"mci-gru-stock-prediction-model-based-on-multi","title":"MCI-GRU: Stock Prediction Model Based on Multi-Head Cross-Attention and Improved GRU","date":"2024-09-25","arxiv_id":"2410.20679","n_code_links":0,"syntology":null},{"paper":null,"slug":"near-field-multipath-mimo-channel-model-for","title":"Near-Field Multipath MIMO Channel Model for Imperfect Surface Reflection","date":"2024-09-25","arxiv_id":"2409.17041","n_code_links":0,"syntology":null},{"paper":null,"slug":"non-asymptotic-convergence-of-training","title":"Non-asymptotic Convergence of Training Transformers for Next-token Prediction","date":"2024-09-25","arxiv_id":"2409.17335","n_code_links":0,"syntology":null},{"paper":null,"slug":"non-stationary-bert-exploring-augmented-imu","title":"Non-stationary BERT: Exploring Augmented IMU Data For Robust Human Activity Recognition","date":"2024-09-25","arxiv_id":"2409.16730","n_code_links":0,"syntology":null},{"paper":"/paper/post-hoc-reward-calibration-a-case-study-on","slug":"post-hoc-reward-calibration-a-case-study-on","title":"Post-hoc Reward Calibration: A Case Study on Length Bias","date":"2024-09-25","arxiv_id":"2409.17407","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":["zeroyuhuang/reward-calibration"],"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":"pre-trained-graphformer-based-ranking-at-web","title":"Pre-trained Graphformer-based Ranking at Web-scale Search (Extended Abstract)","date":"2024-09-25","arxiv_id":"2409.16590","n_code_links":0,"syntology":null},{"paper":null,"slug":"probing-omissions-and-distortions-in","title":"Probing Omissions and Distortions in Transformer-based RDF-to-Text Models","date":"2024-09-25","arxiv_id":"2409.16707","n_code_links":0,"syntology":null},{"paper":null,"slug":"quantum-classical-sentiment-analysis","title":"Quantum-Classical Sentiment Analysis","date":"2024-09-25","arxiv_id":"2409.16928","n_code_links":0,"syntology":null},{"paper":null,"slug":"severity-prediction-in-mental-health-llm","title":"Severity Prediction in Mental Health: LLM-based Creation, Analysis, Evaluation of a Novel Multilingual Dataset","date":"2024-09-25","arxiv_id":"2409.17397","n_code_links":0,"syntology":null},{"paper":null,"slug":"swe2-subword-enriched-and-significant-word","title":"SWE2: SubWord Enriched and Significant Word Emphasized Framework for Hate Speech Detection","date":"2024-09-25","arxiv_id":"2409.16673","n_code_links":0,"syntology":null},{"paper":null,"slug":"the-credibility-transformer","title":"The Credibility Transformer","date":"2024-09-25","arxiv_id":"2409.16653","n_code_links":0,"syntology":null},{"paper":null,"slug":"the-overfocusing-bias-of-convolutional-neural","title":"The Overfocusing Bias of Convolutional Neural Networks: A Saliency-Guided Regularization Approach","date":"2024-09-25","arxiv_id":"2409.17370","n_code_links":0,"syntology":null},{"paper":null,"slug":"the-role-of-language-models-in-modern","title":"The Role of Language Models in Modern Healthcare: A Comprehensive Review","date":"2024-09-25","arxiv_id":"2409.16860","n_code_links":0,"syntology":null},{"paper":null,"slug":"trading-through-earnings-seasons-using-self","title":"Trading through Earnings Seasons using Self-Supervised Contrastive Representation Learning","date":"2024-09-25","arxiv_id":"2409.17392","n_code_links":0,"syntology":null},{"paper":null,"slug":"using-llm-for-real-time-transcription-and","title":"Using LLM for Real-Time Transcription and Summarization of Doctor-Patient Interactions into ePuskesmas in Indonesia","date":"2024-09-25","arxiv_id":"2409.17054","n_code_links":0,"syntology":null},{"paper":"/paper/zero-shot-detection-of-llm-generated-text","slug":"zero-shot-detection-of-llm-generated-text","title":"Zero-Shot Detection of LLM-Generated Text using Token Cohesiveness","date":"2024-09-25","arxiv_id":"2409.16914","n_code_links":1,"syntology":{"ran":2,"of":4,"n_ran_checked":0,"n_instrument":2,"unverified":2,"pointer_only":0,"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) · 2 unverified","official":{"repos":["shixuan-ma/tocsin"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"a-comprehensive-evaluation-of-large-language-3","title":"A Comprehensive Evaluation of Large Language Models on Mental Illnesses","date":"2024-09-24","arxiv_id":"2409.15687","n_code_links":0,"syntology":null},{"paper":null,"slug":"ai-can-be-cognitively-biased-an-exploratory","title":"AI Can Be Cognitively Biased: An Exploratory Study on Threshold Priming in LLM-Based Batch Relevance Assessment","date":"2024-09-24","arxiv_id":"2409.16022","n_code_links":0,"syntology":null},{"paper":null,"slug":"beyond-text-to-text-an-overview-of-multimodal","title":"Beyond Text-to-Text: An Overview of Multimodal and Generative Artificial Intelligence for Education Using Topic Modeling","date":"2024-09-24","arxiv_id":"2409.16376","n_code_links":0,"syntology":null},{"paper":"/paper/controlling-risk-of-retrieval-augmented","slug":"controlling-risk-of-retrieval-augmented","title":"Controlling Risk of Retrieval-augmented Generation: A Counterfactual Prompting Framework","date":"2024-09-24","arxiv_id":"2409.16146","n_code_links":1,"syntology":{"ran":5,"of":8,"n_ran_checked":5,"n_instrument":0,"unverified":3,"pointer_only":8,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","official":{"repos":["ict-bigdatalab/rc-rag"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":"/paper/data-augmentation-for-sparse-multidimensional","slug":"data-augmentation-for-sparse-multidimensional","title":"Data Augmentation for Sparse Multidimensional Learning Performance Data Using Generative AI","date":"2024-09-24","arxiv_id":"2409.15631","n_code_links":1,"syntology":null},{"paper":null,"slug":"disentangled-generation-and-aggregation-for","title":"Disentangled Generation and Aggregation for Robust Radiance Fields","date":"2024-09-24","arxiv_id":"2409.15715","n_code_links":0,"syntology":null},{"paper":null,"slug":"dnagrinder-a-lightweight-and-high-capacity","title":"dnaGrinder: a lightweight and high-capacity genomic foundation model","date":"2024-09-24","arxiv_id":"2409.15697","n_code_links":0,"syntology":null},{"paper":null,"slug":"do-the-right-thing-just-debias-multi-category","title":"Do the Right Thing, Just Debias! Multi-Category Bias Mitigation Using LLMs","date":"2024-09-24","arxiv_id":"2409.16371","n_code_links":0,"syntology":null},{"paper":null,"slug":"double-path-adaptive-correlation-spatial","title":"Double-Path Adaptive-correlation Spatial-Temporal Inverted Transformer for Stock Time Series Forecasting","date":"2024-09-24","arxiv_id":"2409.15662","n_code_links":0,"syntology":null},{"paper":"/paper/ducho-meets-elliot-large-scale-benchmarks-for-1","slug":"ducho-meets-elliot-large-scale-benchmarks-for-1","title":"Ducho meets Elliot: Large-scale Benchmarks for Multimodal Recommendation","date":"2024-09-24","arxiv_id":"2409.15857","n_code_links":1,"syntology":null},{"paper":"/paper/effectiveness-of-cross-linguistic-extraction","slug":"effectiveness-of-cross-linguistic-extraction","title":"Effectiveness of Cross-linguistic Extraction of Genetic Information using Generative Large Language Models","date":"2024-09-24","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"from-pixels-to-words-leveraging","title":"From Pixels to Words: Leveraging Explainability in Face Recognition through Interactive Natural Language Processing","date":"2024-09-24","arxiv_id":"2409.16089","n_code_links":0,"syntology":null},{"paper":null,"slug":"gs-net-global-self-attention-guided-cnn-for","title":"GS-Net: Global Self-Attention Guided CNN for Multi-Stage Glaucoma Classification","date":"2024-09-24","arxiv_id":"2409.16082","n_code_links":0,"syntology":null},{"paper":"/paper/irsc-a-zero-shot-evaluation-benchmark-for","slug":"irsc-a-zero-shot-evaluation-benchmark-for","title":"IRSC: A Zero-shot Evaluation Benchmark for Information Retrieval through Semantic Comprehension in Retrieval-Augmented Generation Scenarios","date":"2024-09-24","arxiv_id":"2409.15763","n_code_links":1,"syntology":null},{"paper":"/paper/language-based-audio-moment-retrieval","slug":"language-based-audio-moment-retrieval","title":"Language-based Audio Moment Retrieval","date":"2024-09-24","arxiv_id":"2409.15672","n_code_links":1,"syntology":null},{"paper":"/paper/lessons-learned-from-a-unifying-empirical","slug":"lessons-learned-from-a-unifying-empirical","title":"Lessons and Insights from a Unifying Study of Parameter-Efficient Fine-Tuning (PEFT) in Visual Recognition","date":"2024-09-24","arxiv_id":"2409.16434","n_code_links":2,"syntology":null},{"paper":null,"slug":"lighter-and-better-towards-flexible-context","title":"Lighter And Better: Towards Flexible Context Adaptation For Retrieval Augmented Generation","date":"2024-09-24","arxiv_id":"2409.15699","n_code_links":0,"syntology":null},{"paper":"/paper/looped-transformers-for-length-generalization","slug":"looped-transformers-for-length-generalization","title":"Looped Transformers for Length Generalization","date":"2024-09-24","arxiv_id":"2409.15647","n_code_links":1,"syntology":{"ran":14,"of":17,"n_ran_checked":14,"n_instrument":0,"unverified":3,"pointer_only":17,"phrase":"14 ran (of which 0 constructed an object rather than computing a result; 14 with no instrument failure: 0 honoured, 0 violated, 14 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","official":{"repos":["uw-madison-lee-lab/looped-tf"],"state":"official (archive's flag): 14 ran","n_ran":14,"n_constructed":0,"n_ran_no_instrument_failure":14,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":"/paper/making-text-embedders-few-shot-learners","slug":"making-text-embedders-few-shot-learners","title":"Making Text Embedders Few-Shot Learners","date":"2024-09-24","arxiv_id":"2409.15700","n_code_links":1,"syntology":null},{"paper":"/paper/maskbit-embedding-free-image-generation-via","slug":"maskbit-embedding-free-image-generation-via","title":"MaskBit: Embedding-free Image Generation via Bit Tokens","date":"2024-09-24","arxiv_id":"2409.16211","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 1 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":["markweberdev/maskbit"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":1,"n_ran_no_instrument_failure":8,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/monoformer-one-transformer-for-both-diffusion","slug":"monoformer-one-transformer-for-both-diffusion","title":"MonoFormer: One Transformer for Both Diffusion and Autoregression","date":"2024-09-24","arxiv_id":"2409.16280","n_code_links":1,"syntology":{"ran":5,"of":8,"n_ran_checked":3,"n_instrument":2,"unverified":3,"pointer_only":8,"phrase":"5 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; 2 where Syntology's instrument failed) · 3 unverified","official":{"repos":["MonoFormer/MonoFormer"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":"/paper/neuromorphic-drone-detection-an-event-rgb","slug":"neuromorphic-drone-detection-an-event-rgb","title":"Neuromorphic Drone Detection: an Event-RGB Multimodal Approach","date":"2024-09-24","arxiv_id":"2409.16099","n_code_links":1,"syntology":null},{"paper":null,"slug":"predicting-deterioration-in-mild-cognitive","title":"Predicting Deterioration in Mild Cognitive Impairment with Survival Transformers, Extreme Gradient Boosting and Cox Proportional Hazard Modelling","date":"2024-09-24","arxiv_id":"2409.16231","n_code_links":0,"syntology":null},{"paper":null,"slug":"predicting-distance-matrix-with-large","title":"Predicting Distance matrix with large language models","date":"2024-09-24","arxiv_id":"2409.16333","n_code_links":0,"syntology":null},{"paper":null,"slug":"selection-of-prompt-engineering-techniques","title":"Selection of Prompt Engineering Techniques for Code Generation through Predicting Code Complexity","date":"2024-09-24","arxiv_id":"2409.16416","n_code_links":0,"syntology":null},{"paper":"/paper/self-attention-as-an-attractor-network","slug":"self-attention-as-an-attractor-network","title":"Self-attention as an attractor network: transient memories without backpropagation","date":"2024-09-24","arxiv_id":"2409.16112","n_code_links":1,"syntology":null},{"paper":null,"slug":"sex-differences-in-hierarchical-and-modular","title":"Sex Differences in Hierarchical and Modular Organization of Functional Brain Networks: Insights from Hierarchical Entropy and Modularity Analysis","date":"2024-09-24","arxiv_id":"2409.15833","n_code_links":0,"syntology":null},{"paper":"/paper/small-language-models-survey-measurements-and","slug":"small-language-models-survey-measurements-and","title":"Small Language Models: Survey, Measurements, and Insights","date":"2024-09-24","arxiv_id":"2409.15790","n_code_links":1,"syntology":null},{"paper":null,"slug":"supervised-fine-tuning-an-activation-pattern","title":"Supervised Fine-Tuning Achieve Rapid Task Adaption Via Alternating Attention Head Activation Patterns","date":"2024-09-24","arxiv_id":"2409.15820","n_code_links":0,"syntology":null},{"paper":null,"slug":"surgirl-towards-life-long-learning-for","title":"SurgIRL: Towards Life-Long Learning for Surgical Automation by Incremental Reinforcement Learning","date":"2024-09-24","arxiv_id":"2409.15651","n_code_links":0,"syntology":null},{"paper":null,"slug":"swiftdossier-tailored-automatic-dossier-for","title":"SwiftDossier: Tailored Automatic Dossier for Drug Discovery with LLMs and Agents","date":"2024-09-24","arxiv_id":"2409.15817","n_code_links":0,"syntology":null},{"paper":null,"slug":"synatra-turning-indirect-knowledge-into","title":"Synatra: Turning Indirect Knowledge into Direct Demonstrations for Digital Agents at Scale","date":"2024-09-24","arxiv_id":"2409.15637","n_code_links":0,"syntology":null},{"paper":null,"slug":"task-oriented-prompt-enhancement-via-script","title":"Task-oriented Prompt Enhancement via Script Generation","date":"2024-09-24","arxiv_id":"2409.16418","n_code_links":0,"syntology":null},{"paper":"/paper/tim4rec-an-efficient-sequential","slug":"tim4rec-an-efficient-sequential","title":"TiM4Rec: An Efficient Sequential Recommendation Model Based on Time-Aware Structured State Space Duality Model","date":"2024-09-24","arxiv_id":"2409.16182","n_code_links":1,"syntology":null},{"paper":null,"slug":"towards-explainable-graph-neural-networks-for","title":"Towards Explainable Graph Neural Networks for Neurological Evaluation on EEG Signals","date":"2024-09-24","arxiv_id":"2410.07199","n_code_links":0,"syntology":null},{"paper":null,"slug":"transformer-based-time-series-prediction-of","title":"Transformer based time series prediction of the maximum power point for solar photovoltaic cells","date":"2024-09-24","arxiv_id":"2409.16342","n_code_links":0,"syntology":null},{"paper":null,"slug":"underground-mapping-and-localization-based-on","title":"Underground Mapping and Localization Based on Ground-Penetrating Radar","date":"2024-09-24","arxiv_id":"2409.16446","n_code_links":0,"syntology":null},{"paper":null,"slug":"unsupervised-attention-regularization-based","title":"Unsupervised Attention Regularization Based Domain Adaptation for Oracle Character Recognition","date":"2024-09-24","arxiv_id":"2409.15893","n_code_links":0,"syntology":null},{"paper":"/paper/videopatchcore-an-effective-method-to","slug":"videopatchcore-an-effective-method-to","title":"VideoPatchCore: An Effective Method to Memorize Normality for Video Anomaly Detection","date":"2024-09-24","arxiv_id":"2409.16225","n_code_links":1,"syntology":null},{"paper":"/paper/wesep-a-scalable-and-flexible-toolkit-towards","slug":"wesep-a-scalable-and-flexible-toolkit-towards","title":"WeSep: A Scalable and Flexible Toolkit Towards Generalizable Target Speaker Extraction","date":"2024-09-24","arxiv_id":"2409.15799","n_code_links":1,"syntology":null},{"paper":"/paper/xtrust-on-the-multilingual-trustworthiness-of","slug":"xtrust-on-the-multilingual-trustworthiness-of","title":"XTRUST: On the Multilingual Trustworthiness of Large Language Models","date":"2024-09-24","arxiv_id":"2409.15762","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-preliminary-study-of-o1-in-medicine-are-we","title":"A Preliminary Study of o1 in Medicine: Are We Closer to an AI Doctor?","date":"2024-09-23","arxiv_id":"2409.15277","n_code_links":0,"syntology":null},{"paper":"/paper/a-vl-adaptive-attention-for-large-vision","slug":"a-vl-adaptive-attention-for-large-vision","title":"A-VL: Adaptive Attention for Large Vision-Language Models","date":"2024-09-23","arxiv_id":"2409.14846","n_code_links":1,"syntology":null},{"paper":null,"slug":"advancing-depression-detection-on-social","title":"Advancing Depression Detection on Social Media Platforms Through Fine-Tuned Large Language Models","date":"2024-09-23","arxiv_id":"2409.14794","n_code_links":0,"syntology":null},{"paper":null,"slug":"aeanet-affinity-enhanced-attentional-networks","title":"AEANet: Affinity Enhanced Attentional Networks for Arbitrary Style Transfer","date":"2024-09-23","arxiv_id":"2409.14652","n_code_links":0,"syntology":null},{"paper":null,"slug":"ca-mhfa-a-context-aware-multi-head-factorized","title":"CA-MHFA: A Context-Aware Multi-Head Factorized Attentive Pooling for SSL-Based Speaker Verification","date":"2024-09-23","arxiv_id":"2409.15234","n_code_links":0,"syntology":null},{"paper":null,"slug":"chattronics-using-gpts-to-assist-in-the","title":"Chattronics: using GPTs to assist in the design of data acquisition systems","date":"2024-09-23","arxiv_id":"2409.15183","n_code_links":0,"syntology":null},{"paper":"/paper/clinical-grade-multi-organ-pathology-report","slug":"clinical-grade-multi-organ-pathology-report","title":"Clinical-grade Multi-Organ Pathology Report Generation for Multi-scale Whole Slide Images via a Semantically Guided Medical Text Foundation Model","date":"2024-09-23","arxiv_id":"2409.15574","n_code_links":1,"syntology":null},{"paper":null,"slug":"curb-your-attention-causal-attention-gating","title":"Curb Your Attention: Causal Attention Gating for Robust Trajectory Prediction in Autonomous Driving","date":"2024-09-23","arxiv_id":"2410.07191","n_code_links":0,"syntology":null},{"paper":null,"slug":"deep-cost-ray-fusion-for-sparse-depth-video","title":"Deep Cost Ray Fusion for Sparse Depth Video Completion","date":"2024-09-23","arxiv_id":"2409.14935","n_code_links":0,"syntology":null},{"paper":null,"slug":"deep-reinforcement-learning-based-obstacle","title":"Deep Reinforcement Learning-based Obstacle Avoidance for Robot Movement in Warehouse Environments","date":"2024-09-23","arxiv_id":"2409.14972","n_code_links":0,"syntology":null},{"paper":null,"slug":"depthart-monocular-depth-estimation-as","title":"DepthART: Monocular Depth Estimation as Autoregressive Refinement Task","date":"2024-09-23","arxiv_id":"2409.15010","n_code_links":0,"syntology":null},{"paper":null,"slug":"designing-pre-training-datasets-from","title":"Designing Pre-training Datasets from Unlabeled Data for EEG Classification with Transformers","date":"2024-09-23","arxiv_id":"2410.07190","n_code_links":0,"syntology":null},{"paper":"/paper/diffusion-based-rgb-d-semantic-segmentation","slug":"diffusion-based-rgb-d-semantic-segmentation","title":"Diffusion-based RGB-D Semantic Segmentation with Deformable Attention Transformer","date":"2024-09-23","arxiv_id":"2409.15117","n_code_links":0,"syntology":null},{"paper":null,"slug":"dual-stream-graph-transformer-fusion-networks","title":"Dual Stream Graph Transformer Fusion Networks for Enhanced Brain Decoding","date":"2024-09-23","arxiv_id":"2410.07189","n_code_links":0,"syntology":null},{"paper":"/paper/dumpling-gnn-hybrid-gnn-enables-better-adc","slug":"dumpling-gnn-hybrid-gnn-enables-better-adc","title":"Dumpling GNN: Hybrid GNN Enables Better ADC Payload Activity Prediction Based on Chemical Structure","date":"2024-09-23","arxiv_id":"2410.05278","n_code_links":0,"syntology":null},{"paper":null,"slug":"edge-rec-efficient-and-data-guided-edge","title":"EDGE-Rec: Efficient and Data-Guided Edge Diffusion For Recommender Systems Graphs","date":"2024-09-23","arxiv_id":"2409.14689","n_code_links":0,"syntology":null}],"record_sha256":"2a5e82786dc7374d6d5952e432a1e280df61fbc742be8b1902cae99248ee0a38","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}