{"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/focus/papers/70","list_of":"/method/focus","method":"Focus","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":70,"pages_in_order":154,"rows_per_page":100,"rows":[6901,7000],"of":15340,"counts":{"archive_papers_tagged":15340,"with_a_code_link":5193,"where_syntology_ran_a_sample":1419,"not_listed_spam_title":0,"listed":15340,"listed_where_code_ran":1419,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":1210,"every_run_a_failure_of_syntologys_instrument":209,"listed_with_a_run_with_no_instrument_failure":1210,"listed_every_run_a_failure_of_syntologys_instrument":209,"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/focus","prev":"/method/focus/papers/69","next":"/method/focus/papers/71","papers":[{"paper":null,"slug":"efficient-exploration-in-deep-reinforcement","title":"Efficient Exploration in Deep Reinforcement Learning: A Novel Bayesian Actor-Critic Algorithm","date":"2024-08-19","arxiv_id":"2408.10055","n_code_links":0,"syntology":null},{"paper":null,"slug":"faster-adaptive-decentralized-learning","title":"Faster Adaptive Decentralized Learning Algorithms","date":"2024-08-19","arxiv_id":"2408.09775","n_code_links":0,"syntology":null},{"paper":"/paper/image-tell-me-your-story-predicting-the","slug":"image-tell-me-your-story-predicting-the","title":"\"Image, Tell me your story!\" Predicting the original meta-context of visual misinformation","date":"2024-08-19","arxiv_id":"2408.09939","n_code_links":1,"syntology":{"ran":15,"of":17,"n_ran_checked":15,"n_instrument":0,"unverified":2,"pointer_only":0,"phrase":"15 ran (of which 0 constructed an object rather than computing a result; 15 with no instrument failure: 0 honoured, 0 violated, 15 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","official":{"repos":["ukplab/5pils"],"state":"official (archive's flag): 15 ran","n_ran":15,"n_constructed":0,"n_ran_no_instrument_failure":15,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"learning-brave-assumption-based-argumentation","title":"Learning Brave Assumption-Based Argumentation Frameworks via ASP","date":"2024-08-19","arxiv_id":"2408.10126","n_code_links":0,"syntology":null},{"paper":null,"slug":"learning-precise-affordances-from-egocentric","title":"Learning Precise Affordances from Egocentric Videos for Robotic Manipulation","date":"2024-08-19","arxiv_id":"2408.10123","n_code_links":0,"syntology":null},{"paper":null,"slug":"machine-learning-with-physics-knowledge-for","title":"Machine Learning with Physics Knowledge for Prediction: A Survey","date":"2024-08-19","arxiv_id":"2408.09840","n_code_links":0,"syntology":null},{"paper":"/paper/ranking-generated-answers-on-the-agreement-of","slug":"ranking-generated-answers-on-the-agreement-of","title":"Ranking Generated Answers: On the Agreement of Retrieval Models with Humans on Consumer Health Questions","date":"2024-08-19","arxiv_id":"2408.09831","n_code_links":1,"syntology":null},{"paper":null,"slug":"toward-large-scale-spiking-neural-networks-a","title":"Toward Large-scale Spiking Neural Networks: A Comprehensive Survey and Future Directions","date":"2024-08-19","arxiv_id":"2409.02111","n_code_links":0,"syntology":null},{"paper":"/paper/tradiffusion-trajectory-based-training-free","slug":"tradiffusion-trajectory-based-training-free","title":"TraDiffusion: Trajectory-Based Training-Free Image Generation","date":"2024-08-19","arxiv_id":"2408.09739","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 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":["och-mac/tradiffusion"],"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/unsupervised-composable-representations-for","slug":"unsupervised-composable-representations-for","title":"Unsupervised Composable Representations for Audio","date":"2024-08-19","arxiv_id":"2408.09792","n_code_links":1,"syntology":null},{"paper":null,"slug":"an-introduction-to-cognidynamics","title":"An Introduction to Cognidynamics","date":"2024-08-18","arxiv_id":"2408.13112","n_code_links":0,"syntology":null},{"paper":null,"slug":"attention-is-not-what-you-need-revisiting","title":"Attention Is Not What You Need: Revisiting Multi-Instance Learning for Whole Slide Image Classification","date":"2024-08-18","arxiv_id":"2408.09449","n_code_links":0,"syntology":null},{"paper":"/paper/enhancing-modal-fusion-by-alignment-and-label","slug":"enhancing-modal-fusion-by-alignment-and-label","title":"Enhancing Modal Fusion by Alignment and Label Matching for Multimodal Emotion Recognition","date":"2024-08-18","arxiv_id":"2408.09438","n_code_links":1,"syntology":null},{"paper":null,"slug":"mergerepair-an-exploratory-study-on-merging","title":"MergeRepair: An Exploratory Study on Merging Task-Specific Adapters in Code LLMs for Automated Program Repair","date":"2024-08-18","arxiv_id":"2408.09568","n_code_links":0,"syntology":null},{"paper":null,"slug":"panorama-tomosynthesis-from-head-cbct-with","title":"Panorama Tomosynthesis from Head CBCT with Simulated Projection Geometry","date":"2024-08-18","arxiv_id":"2408.09358","n_code_links":0,"syntology":null},{"paper":null,"slug":"revisiting-the-graph-reasoning-ability-of","title":"Revisiting the Graph Reasoning Ability of Large Language Models: Case Studies in Translation, Connectivity and Shortest Path","date":"2024-08-18","arxiv_id":"2408.09529","n_code_links":0,"syntology":null},{"paper":null,"slug":"sample-optimal-large-scale-optimal-subset","title":"Efficient Budget Allocation for Large-Scale LLM-Enabled Virtual Screening","date":"2024-08-18","arxiv_id":"2408.09537","n_code_links":0,"syntology":null},{"paper":null,"slug":"unpaired-volumetric-harmonization-of-brain","title":"Unpaired Volumetric Harmonization of Brain MRI with Conditional Latent Diffusion","date":"2024-08-18","arxiv_id":"2408.09315","n_code_links":0,"syntology":null},{"paper":"/paper/automatic-metrics-in-natural-language","slug":"automatic-metrics-in-natural-language","title":"Automatic Metrics in Natural Language Generation: A Survey of Current Evaluation Practices","date":"2024-08-17","arxiv_id":"2408.09169","n_code_links":1,"syntology":null},{"paper":"/paper/benchmarking-quantum-machine-learning-kernel","slug":"benchmarking-quantum-machine-learning-kernel","title":"Benchmarking quantum machine learning kernel training for classification tasks","date":"2024-08-17","arxiv_id":"2408.10274","n_code_links":1,"syntology":null},{"paper":null,"slug":"better-python-programming-for-all-with-the","title":"Better Python Programming for all: With the focus on Maintainability","date":"2024-08-17","arxiv_id":"2408.09134","n_code_links":0,"syntology":null},{"paper":"/paper/dynamic-neural-dowker-network-approximating","slug":"dynamic-neural-dowker-network-approximating","title":"Dynamic Neural Dowker Network: Approximating Persistent Homology in Dynamic Directed Graphs","date":"2024-08-17","arxiv_id":"2408.09123","n_code_links":1,"syntology":null},{"paper":null,"slug":"magicid-flexible-id-fidelity-generation","title":"MagicID: Flexible ID Fidelity Generation System","date":"2024-08-17","arxiv_id":"2408.09248","n_code_links":0,"syntology":null},{"paper":null,"slug":"mambatrack-a-simple-baseline-for-multiple","title":"MambaTrack: A Simple Baseline for Multiple Object Tracking with State Space Model","date":"2024-08-17","arxiv_id":"2408.09178","n_code_links":0,"syntology":null},{"paper":"/paper/premap-a-unifying-preimage-approximation","slug":"premap-a-unifying-preimage-approximation","title":"PREMAP: A Unifying PREiMage APproximation Framework for Neural Networks","date":"2024-08-17","arxiv_id":"2408.09262","n_code_links":1,"syntology":null},{"paper":null,"slug":"pupil-adaptive-3d-holography-beyond-coherent","title":"Pupil-Adaptive 3D Holography Beyond Coherent Depth-of-Field","date":"2024-08-17","arxiv_id":"2409.00028","n_code_links":0,"syntology":null},{"paper":"/paper/scalable-and-certifiable-graph-unlearning-via","slug":"scalable-and-certifiable-graph-unlearning-via","title":"Scalable and Certifiable Graph Unlearning: Overcoming the Approximation Error Barrier","date":"2024-08-17","arxiv_id":"2408.09212","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":["luyi256/ScaleGUN"],"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":null,"slug":"toward-end-to-end-bearing-fault-diagnosis-for","title":"Toward End-to-End Bearing Fault Diagnosis for Industrial Scenarios with Spiking Neural Networks","date":"2024-08-17","arxiv_id":"2408.11067","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-survey-on-secure-decentralized-optimization","title":"A survey on secure decentralized optimization and learning","date":"2024-08-16","arxiv_id":"2408.08628","n_code_links":0,"syntology":null},{"paper":"/paper/adversarial-contrastive-learning-based","slug":"adversarial-contrastive-learning-based","title":"PITN: Physics-Informed Temporal Networks for Cuffless Blood Pressure Estimation","date":"2024-08-16","arxiv_id":"2408.08488","n_code_links":1,"syntology":null},{"paper":"/paper/can-large-language-models-improve-the","slug":"can-large-language-models-improve-the","title":"Can Large Language Models Improve the Adversarial Robustness of Graph Neural Networks?","date":"2024-08-16","arxiv_id":"2408.08685","n_code_links":1,"syntology":null},{"paper":"/paper/chain-of-exemplar-enhancing-distractor","slug":"chain-of-exemplar-enhancing-distractor","title":"Chain-of-Exemplar: Enhancing Distractor Generation for Multimodal Educational Question Generation","date":"2024-08-16","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"collaborative-cross-modal-fusion-with-large","title":"Collaborative Cross-modal Fusion with Large Language Model for Recommendation","date":"2024-08-16","arxiv_id":"2408.08564","n_code_links":0,"syntology":null},{"paper":null,"slug":"constructing-domain-specific-evaluation-sets","title":"Constructing Domain-Specific Evaluation Sets for LLM-as-a-judge","date":"2024-08-16","arxiv_id":"2408.08808","n_code_links":0,"syntology":null},{"paper":null,"slug":"eraw-net-enhance-refine-align-w-net-for-scene","title":"EraW-Net: Enhance-Refine-Align W-Net for Scene-Associated Driver Attention Estimation","date":"2024-08-16","arxiv_id":"2408.08570","n_code_links":0,"syntology":null},{"paper":"/paper/focus-on-focus-focus-oriented-representation","slug":"focus-on-focus-focus-oriented-representation","title":"Focus on Focus: Focus-oriented Representation Learning and Multi-view Cross-modal Alignment for Glioma Grading","date":"2024-08-16","arxiv_id":"2408.08527","n_code_links":1,"syntology":null},{"paper":"/paper/generative-dataset-distillation-based-on","slug":"generative-dataset-distillation-based-on","title":"Generative Dataset Distillation Based on Diffusion Model","date":"2024-08-16","arxiv_id":"2408.08610","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 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) · 0 unverified","official":{"repos":["Guang000/Awesome-Dataset-Distillation","guang000/banko"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/med-pmc-medical-personalized-multi-modal","slug":"med-pmc-medical-personalized-multi-modal","title":"Med-PMC: Medical Personalized Multi-modal Consultation with a Proactive Ask-First-Observe-Next Paradigm","date":"2024-08-16","arxiv_id":"2408.08693","n_code_links":1,"syntology":{"ran":8,"of":8,"n_ran_checked":6,"n_instrument":2,"unverified":0,"pointer_only":8,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["liuhc0428/med-pmc"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"misclassification-excess-risk-bounds-for-pac","title":"Misclassification excess risk bounds for PAC-Bayesian classification via convexified loss","date":"2024-08-16","arxiv_id":"2408.08675","n_code_links":0,"syntology":null},{"paper":null,"slug":"multimodal-relational-triple-extraction-with","title":"Multimodal Relational Triple Extraction with Query-based Entity Object Transformer","date":"2024-08-16","arxiv_id":"2408.08709","n_code_links":0,"syntology":null},{"paper":null,"slug":"murar-a-simple-and-effective-multimodal","title":"MuRAR: A Simple and Effective Multimodal Retrieval and Answer Refinement Framework for Multimodal Question Answering","date":"2024-08-16","arxiv_id":"2408.08521","n_code_links":0,"syntology":null},{"paper":null,"slug":"quantifying-the-effectiveness-of-student","title":"Quantifying the Effectiveness of Student Organization Activities using Natural Language Processing","date":"2024-08-16","arxiv_id":"2408.08694","n_code_links":0,"syntology":null},{"paper":null,"slug":"research-on-personalized-compression","title":"Research on Personalized Compression Algorithm for Pre-trained Models Based on Homomorphic Entropy Increase","date":"2024-08-16","arxiv_id":"2408.08684","n_code_links":0,"syntology":null},{"paper":null,"slug":"systemic-values-at-risk-and-their-sample","title":"Systemic values-at-risk and their sample-average approximations","date":"2024-08-16","arxiv_id":"2408.08511","n_code_links":0,"syntology":null},{"paper":null,"slug":"tell-codec-what-worth-compressing","title":"Tell Codec What Worth Compressing: Semantically Disentangled Image Coding for Machine with LMMs","date":"2024-08-16","arxiv_id":"2408.08575","n_code_links":0,"syntology":null},{"paper":null,"slug":"an-efficient-continuous-control-perspective","title":"An Efficient Continuous Control Perspective for Reinforcement-Learning-based Sequential Recommendation","date":"2024-08-15","arxiv_id":"2408.08047","n_code_links":0,"syntology":null},{"paper":"/paper/co-fix3d-enhancing-3d-object-detection-with","slug":"co-fix3d-enhancing-3d-object-detection-with","title":"Co-Fix3D: Enhancing 3D Object Detection with Collaborative Refinement","date":"2024-08-15","arxiv_id":"2408.07999","n_code_links":1,"syntology":null},{"paper":"/paper/corradaptor-adaptive-local-context-learning","slug":"corradaptor-adaptive-local-context-learning","title":"CorrAdaptor: Adaptive Local Context Learning for Correspondence Pruning","date":"2024-08-15","arxiv_id":"2408.08134","n_code_links":1,"syntology":null},{"paper":null,"slug":"evaluating-text-classification-robustness-to","title":"Evaluating Text Classification Robustness to Part-of-Speech Adversarial Examples","date":"2024-08-15","arxiv_id":"2408.08374","n_code_links":0,"syntology":null},{"paper":"/paper/experimental-evaluation-of-offline","slug":"experimental-evaluation-of-offline","title":"Experimental evaluation of offline reinforcement learning for HVAC control in buildings","date":"2024-08-15","arxiv_id":"2408.07986","n_code_links":1,"syntology":null},{"paper":null,"slug":"exploring-learning-environments-for-label","title":"Exploring learning environments for label\\-efficient cancer diagnosis","date":"2024-08-15","arxiv_id":"2408.07988","n_code_links":0,"syntology":null},{"paper":null,"slug":"federated-sequence-to-sequence-learning-for","title":"Federated Sequence-to-Sequence Learning for Load Disaggregation from Unbalanced Low-Resolution Smart Meter Data","date":"2024-08-15","arxiv_id":"2409.00007","n_code_links":0,"syntology":null},{"paper":"/paper/from-clicks-to-carbon-the-environmental-toll","slug":"from-clicks-to-carbon-the-environmental-toll","title":"From Clicks to Carbon: The Environmental Toll of Recommender Systems","date":"2024-08-15","arxiv_id":"2408.08203","n_code_links":1,"syntology":null},{"paper":"/paper/iiu-independent-inference-units-for-knowledge","slug":"iiu-independent-inference-units-for-knowledge","title":"IIU: Independent Inference Units for Knowledge-based Visual Question Answering","date":"2024-08-15","arxiv_id":"2408.07989","n_code_links":1,"syntology":null},{"paper":null,"slug":"independent-policy-mirror-descent-for-markov","title":"Independent Policy Mirror Descent for Markov Potential Games: Scaling to Large Number of Players","date":"2024-08-15","arxiv_id":"2408.08075","n_code_links":0,"syntology":null},{"paper":null,"slug":"is-knowledge-power-on-the-im-possibility-of","title":"Is Knowledge Power? On the (Im)possibility of Learning from Strategic Interactions","date":"2024-08-15","arxiv_id":"2408.08272","n_code_links":0,"syntology":null},{"paper":null,"slug":"learned-multimodal-compression-for-autonomous","title":"Learned Multimodal Compression for Autonomous Driving","date":"2024-08-15","arxiv_id":"2408.08211","n_code_links":0,"syntology":null},{"paper":"/paper/metr-image-watermarking-with-large-number-of","slug":"metr-image-watermarking-with-large-number-of","title":"METR: Image Watermarking with Large Number of Unique Messages","date":"2024-08-15","arxiv_id":"2408.08340","n_code_links":1,"syntology":null},{"paper":null,"slug":"mvinpainter-learning-multi-view-consistent","title":"MVInpainter: Learning Multi-View Consistent Inpainting to Bridge 2D and 3D Editing","date":"2024-08-15","arxiv_id":"2408.08000","n_code_links":0,"syntology":null},{"paper":null,"slug":"not-every-image-is-worth-a-thousand-words","title":"Not Every Image is Worth a Thousand Words: Quantifying Originality in Stable Diffusion","date":"2024-08-15","arxiv_id":"2408.08184","n_code_links":0,"syntology":null},{"paper":null,"slug":"plan-with-code-comparing-approaches-for","title":"Plan with Code: Comparing approaches for robust NL to DSL generation","date":"2024-08-15","arxiv_id":"2408.08335","n_code_links":0,"syntology":null},{"paper":"/paper/slca-unleash-the-power-of-sequential-fine","slug":"slca-unleash-the-power-of-sequential-fine","title":"SLCA++: Unleash the Power of Sequential Fine-tuning for Continual Learning with Pre-training","date":"2024-08-15","arxiv_id":"2408.08295","n_code_links":1,"syntology":{"ran":5,"of":6,"n_ran_checked":3,"n_instrument":2,"unverified":1,"pointer_only":2,"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) · 1 unverified","official":{"repos":["gengdavid/slca"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"system-states-forecasting-of-microservices","title":"System States Forecasting of Microservices with Dynamic Spatio-Temporal Data","date":"2024-08-15","arxiv_id":"2408.07894","n_code_links":0,"syntology":null},{"paper":"/paper/the-dawn-of-kan-in-image-to-image-i2i","slug":"the-dawn-of-kan-in-image-to-image-i2i","title":"The Dawn of KAN in Image-to-Image (I2I) Translation: Integrating Kolmogorov-Arnold Networks with GANs for Unpaired I2I Translation","date":"2024-08-15","arxiv_id":"2408.08216","n_code_links":1,"syntology":null},{"paper":null,"slug":"the-z-gromov-wasserstein-distance","title":"The Z-Gromov-Wasserstein Distance","date":"2024-08-15","arxiv_id":"2408.08233","n_code_links":0,"syntology":null},{"paper":null,"slug":"timing-analysis-and-priority-driven","title":"Timing Analysis and Priority-driven Enhancements of ROS 2 Multi-threaded Executors","date":"2024-08-15","arxiv_id":"2408.08440","n_code_links":0,"syntology":null},{"paper":"/paper/treat-stillness-with-movement-remote-sensing","slug":"treat-stillness-with-movement-remote-sensing","title":"Treat Stillness with Movement: Remote Sensing Change Detection via Coarse-grained Temporal Foregrounds Mining","date":"2024-08-15","arxiv_id":"2408.08078","n_code_links":1,"syntology":null},{"paper":"/paper/unsupervised-part-discovery-via-dual","slug":"unsupervised-part-discovery-via-dual","title":"Unsupervised Part Discovery via Dual Representation Alignment","date":"2024-08-15","arxiv_id":"2408.08108","n_code_links":1,"syntology":null},{"paper":null,"slug":"when-raw-data-prevails-are-large-language","title":"When Raw Data Prevails: Are Large Language Model Embeddings Effective in Numerical Data Representation for Medical Machine Learning Applications?","date":"2024-08-15","arxiv_id":"2408.11854","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-study-on-bias-detection-and-classification","title":"A Study on Bias Detection and Classification in Natural Language Processing","date":"2024-08-14","arxiv_id":"2408.07479","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-system-for-automated-unit-test-generation","title":"A System for Automated Unit Test Generation Using Large Language Models and Assessment of Generated Test Suites","date":"2024-08-14","arxiv_id":"2408.07846","n_code_links":0,"syntology":null},{"paper":null,"slug":"artificial-intelligence-in-power-system","title":"Artificial Intelligence in Power System Security and Stability Analysis: A Comprehensive Review","date":"2024-08-14","arxiv_id":"2408.08914","n_code_links":0,"syntology":null},{"paper":"/paper/assessing-the-role-of-lexical-semantics-in","slug":"assessing-the-role-of-lexical-semantics-in","title":"Assessing the Role of Lexical Semantics in Cross-lingual Transfer through Controlled Manipulations","date":"2024-08-14","arxiv_id":"2408.07599","n_code_links":1,"syntology":null},{"paper":null,"slug":"automated-retinal-image-analysis-and-medical","title":"Automated Retinal Image Analysis and Medical Report Generation through Deep Learning","date":"2024-08-14","arxiv_id":"2408.07349","n_code_links":0,"syntology":null},{"paper":null,"slug":"cognitive-networks-and-performance-drive-fmri","title":"Cognitive Networks and Performance Drive fMRI-Based State Classification Using DNN Models","date":"2024-08-14","arxiv_id":"2409.00003","n_code_links":0,"syntology":null},{"paper":null,"slug":"disentangle-and-denoise-tackling-context","title":"Disentangle and denoise: Tackling context misalignment for video moment retrieval","date":"2024-08-14","arxiv_id":"2408.07600","n_code_links":0,"syntology":null},{"paper":null,"slug":"dpsnn-spiking-neural-network-for-low-latency","title":"DPSNN: Spiking Neural Network for Low-Latency Streaming Speech Enhancement","date":"2024-08-14","arxiv_id":"2408.07388","n_code_links":0,"syntology":null},{"paper":null,"slug":"gqe-generalized-query-expansion-for-enhanced","title":"Bridging Information Asymmetry in Text-video Retrieval: A Data-centric Approach","date":"2024-08-14","arxiv_id":"2408.07249","n_code_links":0,"syntology":null},{"paper":null,"slug":"magicface-training-free-universal-style-human","title":"MagicFace: Training-free Universal-Style Human Image Customized Synthesis","date":"2024-08-14","arxiv_id":"2408.07433","n_code_links":0,"syntology":null},{"paper":"/paper/multi-task-heterogeneous-graph-learning-on","slug":"multi-task-heterogeneous-graph-learning-on","title":"Multi-task Heterogeneous Graph Learning on Electronic Health Records","date":"2024-08-14","arxiv_id":"2408.07569","n_code_links":1,"syntology":{"ran":1,"of":2,"n_ran_checked":1,"n_instrument":0,"unverified":1,"pointer_only":2,"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) · 1 unverified","official":{"repos":["hku-medai/mult-ehr"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/perspectives-comparison-of-deep-learning","slug":"perspectives-comparison-of-deep-learning","title":"Perspectives: Comparison of Deep Learning Segmentation Models on Biophysical and Biomedical Data","date":"2024-08-14","arxiv_id":"2408.07786","n_code_links":1,"syntology":null},{"paper":null,"slug":"planning-with-owl-dl-ontologies-extended","title":"Planning with OWL-DL Ontologies (Extended Version)","date":"2024-08-14","arxiv_id":"2408.07544","n_code_links":0,"syntology":null},{"paper":null,"slug":"rsea-mvgnn-multi-view-graph-neural-network","title":"RSEA-MVGNN: Multi-View Graph Neural Network with Reliable Structural Enhancement and Aggregation","date":"2024-08-14","arxiv_id":"2408.07331","n_code_links":0,"syntology":null},{"paper":null,"slug":"rtat-a-robust-two-stage-association-tracker","title":"RTAT: A Robust Two-stage Association Tracker for Multi-Object Tracking","date":"2024-08-14","arxiv_id":"2408.07344","n_code_links":0,"syntology":null},{"paper":"/paper/sign-language-recognition-based-on-deep","slug":"sign-language-recognition-based-on-deep","title":"Sign language recognition based on deep learning and low-cost handcrafted descriptors","date":"2024-08-14","arxiv_id":"2408.07244","n_code_links":1,"syntology":null},{"paper":null,"slug":"towards-fair-and-rigorous-evaluations","title":"Towards Fair and Rigorous Evaluations: Hyperparameter Optimization for Top-N Recommendation Task with Implicit Feedback","date":"2024-08-14","arxiv_id":"2408.07630","n_code_links":0,"syntology":null},{"paper":null,"slug":"training-language-models-on-the-knowledge","title":"Training Language Models on the Knowledge Graph: Insights on Hallucinations and Their Detectability","date":"2024-08-14","arxiv_id":"2408.07852","n_code_links":0,"syntology":null},{"paper":"/paper/wasserstein-gradient-flows-of-mmd-functionals","slug":"wasserstein-gradient-flows-of-mmd-functionals","title":"Wasserstein Gradient Flows of MMD Functionals with Distance Kernel and Cauchy Problems on Quantile Functions","date":"2024-08-14","arxiv_id":"2408.07498","n_code_links":1,"syntology":{"ran":5,"of":5,"n_ran_checked":2,"n_instrument":3,"unverified":0,"pointer_only":5,"phrase":"5 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; 3 where Syntology's instrument failed) · 0 unverified","official":{"repos":["ViktorAJStein/MMD_Wasserstein_gradient_flow_on_the_line"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"attention-based-feature-fusion-network-for","title":"Attention Based Feature Fusion Network for Monkeypox Skin Lesion Detection","date":"2024-08-13","arxiv_id":"2408.06640","n_code_links":0,"syntology":null},{"paper":"/paper/crome-cross-modal-adapters-for-efficient","slug":"crome-cross-modal-adapters-for-efficient","title":"CROME: Cross-Modal Adapters for Efficient Multimodal LLM","date":"2024-08-13","arxiv_id":"2408.06610","n_code_links":0,"syntology":null},{"paper":null,"slug":"detecting-audio-visual-deepfakes-with-fine","title":"Detecting Audio-Visual Deepfakes with Fine-Grained Inconsistencies","date":"2024-08-13","arxiv_id":"2408.06753","n_code_links":0,"syntology":null},{"paper":null,"slug":"enhancing-multiview-synergy-robust-learning","title":"Enhancing Multiview Synergy: Robust Learning by Exploiting the Wave Loss Function with Consensus and Complementarity Principles","date":"2024-08-13","arxiv_id":"2408.06819","n_code_links":0,"syntology":null},{"paper":null,"slug":"entendre-a-social-bot-detection-tool-for","title":"Entendre, a Social Bot Detection Tool for Niche, Fringe, and Extreme Social Media","date":"2024-08-13","arxiv_id":"2408.06900","n_code_links":0,"syntology":null},{"paper":null,"slug":"heavy-ball-momentum-accelerated-actor-critic","title":"Heavy-Ball Momentum Accelerated Actor-Critic With Function Approximation","date":"2024-08-13","arxiv_id":"2408.06945","n_code_links":0,"syntology":null},{"paper":"/paper/imgcn-interpretable-masked-graph-convolution","slug":"imgcn-interpretable-masked-graph-convolution","title":"IMGCN: Interpretable Masked Graph Convolution Network for Pedestrian Trajectory Prediction","date":"2024-08-13","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/improving-synthetic-image-detection-towards","slug":"improving-synthetic-image-detection-towards","title":"Improving Synthetic Image Detection Towards Generalization: An Image Transformation Perspective","date":"2024-08-13","arxiv_id":"2408.06741","n_code_links":1,"syntology":{"ran":8,"of":9,"n_ran_checked":6,"n_instrument":2,"unverified":1,"pointer_only":3,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","official":{"repos":["ouxiang-li/safe"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/integrating-saliency-ranking-and","slug":"integrating-saliency-ranking-and","title":"Integrating Saliency Ranking and Reinforcement Learning for Enhanced Object Detection","date":"2024-08-13","arxiv_id":"2408.06803","n_code_links":1,"syntology":null},{"paper":"/paper/kan-you-see-it-kans-and-sentinel-for","slug":"kan-you-see-it-kans-and-sentinel-for","title":"KAN You See It? KANs and Sentinel for Effective and Explainable Crop Field Segmentation","date":"2024-08-13","arxiv_id":"2408.07040","n_code_links":1,"syntology":null},{"paper":null,"slug":"language-models-as-models-of-language","title":"Language Models as Models of Language","date":"2024-08-13","arxiv_id":"2408.07144","n_code_links":0,"syntology":null},{"paper":"/paper/mair-improving-multi-view-attention-inverse","slug":"mair-improving-multi-view-attention-inverse","title":"MAIR++: Improving Multi-view Attention Inverse Rendering with Implicit Lighting Representation","date":"2024-08-13","arxiv_id":"2408.06707","n_code_links":1,"syntology":null}],"record_sha256":"2aa26f85ce75ad8d094150c922fcd0b345078848d6e829d0db76180bbff6ede3","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}