{"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":"/task/domain-adaptation/papers/28","list_of":"/task/domain-adaptation","task":"Domain Adaptation","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":28,"pages_in_order":65,"rows_per_page":100,"rows":[2701,2800],"of":6439,"counts":{"archive_papers_tagged":6439,"with_a_code_link":2400,"where_syntology_ran_a_sample":517,"not_listed_spam_title":0,"listed":6439,"listed_where_code_ran":517,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":442,"every_run_a_failure_of_syntologys_instrument":75,"listed_with_a_run_with_no_instrument_failure":442,"listed_every_run_a_failure_of_syntologys_instrument":75,"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":"/task/domain-adaptation","prev":"/task/domain-adaptation/papers/27","next":"/task/domain-adaptation/papers/29","papers":[{"url":null,"slug":"domain-generalization-in-autonomous-driving","title":"Domain Generalization in Autonomous Driving: Evaluating YOLOv8s, RT-DETR, and YOLO-NAS with the ROAD-Almaty Dataset","date":"2024-12-16","arxiv_id":"2412.12349","repositories_listed":0,"syntology":null},{"url":null,"slug":"higda-hierarchical-graph-of-nodes-to-learn","title":"HiGDA: Hierarchical Graph of Nodes to Learn Local-to-Global Topology for Semi-Supervised Domain Adaptation","date":"2024-12-16","arxiv_id":"2412.11819","repositories_listed":0,"syntology":null},{"url":null,"slug":"transliterated-zero-shot-domain-adaptation","title":"Transliterated Zero-Shot Domain Adaptation for Automatic Speech Recognition","date":"2024-12-15","arxiv_id":"2412.11185","repositories_listed":0,"syntology":null},{"url":"/paper/a-universal-degradation-based-bridging","slug":"a-universal-degradation-based-bridging","title":"A Universal Degradation-based Bridging Technique for Domain Adaptive Semantic Segmentation","date":"2024-12-13","arxiv_id":"2412.10339","repositories_listed":0,"syntology":{"n":10,"n_ran":9,"n_constructed":0,"n_ran_checked":6,"n_instrument":3,"n_unverified":1,"n_honours":2,"n_violates":3,"n_no_contract":1,"n_pointer_only":10,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 2 honoured, 3 violated, 1 with no contract checked; 3 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/a-universal-degradation-based-bridging#ran","syntology_url":"https://syntology.ai/paper/2412.10339","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2412.10339"}},"official":null}},{"url":null,"slug":"ttaq-towards-stable-post-training","title":"TTAQ: Towards Stable Post-training Quantization in Continuous Domain Adaptation","date":"2024-12-13","arxiv_id":"2412.09899","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-robust-and-fair-vision-learning-in","title":"Towards Robust and Fair Vision Learning in Open-World Environments","date":"2024-12-12","arxiv_id":"2412.09439","repositories_listed":0,"syntology":null},{"url":null,"slug":"vlms-meet-uda-boosting-transferability-of","title":"VLMs meet UDA: Boosting Transferability of Open Vocabulary Segmentation with Unsupervised Domain Adaptation","date":"2024-12-12","arxiv_id":"2412.09240","repositories_listed":0,"syntology":null},{"url":null,"slug":"adaptive-2-adaptive-domain-mining-for-fine","title":"Adaptive$^2$: Adaptive Domain Mining for Fine-grained Domain Adaptation Modeling","date":"2024-12-11","arxiv_id":"2412.08198","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-radioisotope-identification-in","title":"Enhancing radioisotope identification in gamma spectra via supervised domain adaptation","date":"2024-12-10","arxiv_id":"2412.07069","repositories_listed":0,"syntology":null},{"url":null,"slug":"unlocking-trilevel-learning-with-level-wise","title":"Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence","date":"2024-12-10","arxiv_id":"2412.07138","repositories_listed":0,"syntology":null},{"url":null,"slug":"effective-text-adaptation-for-llm-based-asr","title":"Effective Text Adaptation for LLM-based ASR through Soft Prompt Fine-Tuning","date":"2024-12-09","arxiv_id":"2412.06967","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-device-self-supervised-learning-of-low","title":"On-Device Self-Supervised Learning of Low-Latency Monocular Depth from Only Events","date":"2024-12-09","arxiv_id":"2412.06359","repositories_listed":0,"syntology":null},{"url":null,"slug":"1-800-shared-tasks-at-regnlp-lexical","title":"1-800-SHARED-TASKS at RegNLP: Lexical Reranking of Semantic Retrieval (LeSeR) for Regulatory Question Answering","date":"2024-12-08","arxiv_id":"2412.06009","repositories_listed":0,"syntology":null},{"url":null,"slug":"eeg-based-mental-imagery-task-adaptation-via","title":"EEG-Based Mental Imagery Task Adaptation via Ensemble of Weight-Decomposed Low-Rank Adapters","date":"2024-12-08","arxiv_id":"2412.17818","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-understanding-the-role-of-sharpness","title":"Towards Understanding the Role of Sharpness-Aware Minimization Algorithms for Out-of-Distribution Generalization","date":"2024-12-06","arxiv_id":"2412.05169","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-whole-slide-image-classification","title":"Enhancing Whole Slide Image Classification through Supervised Contrastive Domain Adaptation","date":"2024-12-05","arxiv_id":"2412.04260","repositories_listed":0,"syntology":null},{"url":null,"slug":"redstone-curating-general-code-math-and-qa","title":"RedStone: Curating General, Code, Math, and QA Data for Large Language Models","date":"2024-12-04","arxiv_id":"2412.03398","repositories_listed":0,"syntology":null},{"url":null,"slug":"semi-supervised-transfer-boosting-ss","title":"Semi-Supervised Transfer Boosting (SS-TrBoosting)","date":"2024-12-04","arxiv_id":"2412.03212","repositories_listed":0,"syntology":null},{"url":null,"slug":"ah-ocda-amplitude-based-curriculum-learning","title":"AH-OCDA: Amplitude-based Curriculum Learning and Hopfield Segmentation Model for Open Compound Domain Adaptation","date":"2024-12-03","arxiv_id":"2412.02280","repositories_listed":0,"syntology":null},{"url":null,"slug":"genmix-effective-data-augmentation-with","title":"GenMix: Effective Data Augmentation with Generative Diffusion Model Image Editing","date":"2024-12-03","arxiv_id":"2412.02366","repositories_listed":0,"syntology":null},{"url":null,"slug":"crisp-object-pose-and-shape-estimation-with","title":"CRISP: Object Pose and Shape Estimation with Test-Time Adaptation","date":"2024-12-02","arxiv_id":"2412.01052","repositories_listed":0,"syntology":null},{"url":null,"slug":"cross-domain-adaptation-using-adversarial","title":"Cross Domain Adaptation using Adversarial networks with Cyclic loss","date":"2024-12-02","arxiv_id":"2412.01935","repositories_listed":0,"syntology":null},{"url":null,"slug":"domain-adaptive-diabetic-retinopathy-grading","title":"Domain Adaptive Diabetic Retinopathy Grading with Model Absence and Flowing Data","date":"2024-12-02","arxiv_id":"2412.01203","repositories_listed":0,"syntology":null},{"url":null,"slug":"second-frcsyn-ongoing-winning-solutions-and","title":"Second FRCSyn-onGoing: Winning Solutions and Post-Challenge Analysis to Improve Face Recognition with Synthetic Data","date":"2024-12-02","arxiv_id":"2412.01383","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-the-generalization-capability-of","title":"Enhancing the Generalization Capability of Skin Lesion Classification Models with Active Domain Adaptation Methods","date":"2024-12-01","arxiv_id":"2412.00702","repositories_listed":0,"syntology":null},{"url":null,"slug":"seqwen-at-the-financial-misinformation","title":"SeQwen at the Financial Misinformation Detection Challenge Task: Sequential Learning for Claim Verification and Explanation Generation in Financial Domains","date":"2024-11-30","arxiv_id":"2412.00549","repositories_listed":0,"syntology":null},{"url":null,"slug":"actions-and-objects-pathways-for-domain","title":"Actions and Objects Pathways for Domain Adaptation in Video Question Answering","date":"2024-11-29","arxiv_id":"2411.19434","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-ai-microscopy-for-foodborne","title":"Enhancing AI microscopy for foodborne bacterial classification via adversarial domain adaptation across optical and biological variability","date":"2024-11-29","arxiv_id":"2411.19514","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-data-fusion-based-source-free-semi","title":"Knowledge-Data Fusion Based Source-Free Semi-Supervised Domain Adaptation for Seizure Subtype Classification","date":"2024-11-29","arxiv_id":"2411.19502","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-domain-specific-post-training-for","title":"On Domain-Specific Post-Training for Multimodal Large Language Models","date":"2024-11-29","arxiv_id":"2411.19930","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantifying-the-synthetic-and-real-domain-gap","title":"Quantifying the synthetic and real domain gap in aerial scene understanding","date":"2024-11-29","arxiv_id":"2411.19913","repositories_listed":0,"syntology":null},{"url":null,"slug":"scalable-out-of-distribution-robustness-in","title":"Scalable Out-of-distribution Robustness in the Presence of Unobserved Confounders","date":"2024-11-29","arxiv_id":"2411.19923","repositories_listed":0,"syntology":null},{"url":null,"slug":"zero-forget-preservation-of-semantic","title":"Zero-Forget Preservation of Semantic Communication Alignment in Distributed AI Networks","date":"2024-11-28","arxiv_id":"2411.19385","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-document-ai-data-generation-through","title":"Enhancing Document AI Data Generation Through Graph-Based Synthetic Layouts","date":"2024-11-27","arxiv_id":"2412.03590","repositories_listed":0,"syntology":null},{"url":null,"slug":"thai-financial-domain-adaptation-of-thalle","title":"Thai Financial Domain Adaptation of THaLLE -- Technical Report","date":"2024-11-27","arxiv_id":"2411.18242","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-last-mile-to-supervised-performance-semi","title":"The Last Mile to Supervised Performance: Semi-Supervised Domain Adaptation for Semantic Segmentation","date":"2024-11-27","arxiv_id":"2411.18728","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-generalization-of-handwritten-text","title":"On the Generalization of Handwritten Text Recognition Models","date":"2024-11-26","arxiv_id":"2411.17332","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-study-on-unsupervised-domain-adaptation-for","title":"A Study on Unsupervised Domain Adaptation for Semantic Segmentation in the Era of Vision-Language Models","date":"2024-11-25","arxiv_id":"2411.16407","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-granularity-class-prototype-topology","title":"Multi-Granularity Class Prototype Topology Distillation for Class-Incremental Source-Free Unsupervised Domain Adaptation","date":"2024-11-25","arxiv_id":"2411.16064","repositories_listed":0,"syntology":null},{"url":null,"slug":"drive-dual-robustness-via-information","title":"DRIVE: Dual-Robustness via Information Variability and Entropic Consistency in Source-Free Unsupervised Domain Adaptation","date":"2024-11-24","arxiv_id":"2411.15976","repositories_listed":0,"syntology":null},{"url":null,"slug":"unveiling-the-superior-paradigm-a-comparative","title":"Unveiling the Superior Paradigm: A Comparative Study of Source-Free Domain Adaptation and Unsupervised Domain Adaptation","date":"2024-11-24","arxiv_id":"2411.15844","repositories_listed":0,"syntology":null},{"url":null,"slug":"laguna-language-guided-unsupervised","title":"LAGUNA: LAnguage Guided UNsupervised Adaptation with structured spaces","date":"2024-11-23","arxiv_id":"2411.15557","repositories_listed":0,"syntology":null},{"url":null,"slug":"physically-interpretable-probabilistic-domain","title":"Physically Interpretable Probabilistic Domain Characterization","date":"2024-11-22","arxiv_id":"2411.14827","repositories_listed":0,"syntology":null},{"url":null,"slug":"graph-domain-adaptation-with-dual-branch","title":"Graph Domain Adaptation with Dual-branch Encoder and Two-level Alignment for Whole Slide Image-based Survival Prediction","date":"2024-11-21","arxiv_id":"2411.14001","repositories_listed":0,"syntology":null},{"url":null,"slug":"aglp-a-graph-learning-perspective-for-semi","title":"AGLP: A Graph Learning Perspective for Semi-supervised Domain Adaptation","date":"2024-11-20","arxiv_id":"2411.13152","repositories_listed":0,"syntology":null},{"url":null,"slug":"domain-adaptive-unfolded-graph-neural","title":"Domain Adaptive Unfolded Graph Neural Networks","date":"2024-11-20","arxiv_id":"2411.13137","repositories_listed":0,"syntology":null},{"url":null,"slug":"emergence-of-implicit-world-models-from","title":"Emergence of Implicit World Models from Mortal Agents","date":"2024-11-19","arxiv_id":"2411.12304","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-from-label-proportions-and-covariate","title":"Learning from Label Proportions and Covariate-shifted Instances","date":"2024-11-19","arxiv_id":"2411.12334","repositories_listed":0,"syntology":null},{"url":null,"slug":"impact-gnn-imposing-invariance-with-message","title":"IMPaCT GNN: Imposing invariance with Message Passing in Chronological split Temporal Graphs","date":"2024-11-17","arxiv_id":"2411.10957","repositories_listed":0,"syntology":null},{"url":null,"slug":"bilingual-text-dependent-speaker-verification","title":"Bilingual Text-dependent Speaker Verification with Pre-trained Models for TdSV Challenge 2024","date":"2024-11-16","arxiv_id":"2411.10828","repositories_listed":0,"syntology":null},{"url":null,"slug":"domain-adaptation-based-edge-computing-for","title":"Domain Adaptation-based Edge Computing for Cross-Conditions Fault Diagnosis","date":"2024-11-15","arxiv_id":"2411.10340","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-financial-domain-adaptation-of","title":"Enhancing Financial Domain Adaptation of Language Models via Model Augmentation","date":"2024-11-14","arxiv_id":"2411.09249","repositories_listed":0,"syntology":null},{"url":null,"slug":"tldr-traffic-light-detection-using-fourier","title":"TLDR: Traffic Light Detection using Fourier Domain Adaptation in Hostile WeatheR","date":"2024-11-12","arxiv_id":"2411.07901","repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-unsupervised-domain-adaptation","title":"Efficient Unsupervised Domain Adaptation Regression for Spatial-Temporal Air Quality Sensor Fusion","date":"2024-11-11","arxiv_id":"2411.06917","repositories_listed":0,"syntology":null},{"url":null,"slug":"gradual-fine-tuning-with-graph-routing-for","title":"Gradual Fine-Tuning with Graph Routing for Multi-Source Unsupervised Domain Adaptation","date":"2024-11-11","arxiv_id":"2411.07185","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-from-different-samples-a-source-free","title":"Learning from Different Samples: A Source-free Framework for Semi-supervised Domain Adaptation","date":"2024-11-11","arxiv_id":"2411.06665","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-from-limited-and-imperfect-data","title":"Learning from Limited and Imperfect Data","date":"2024-11-11","arxiv_id":"2411.07229","repositories_listed":0,"syntology":null},{"url":null,"slug":"building-an-efficient-multilingual-non-profit","title":"Building an Efficient Multilingual Non-Profit IR System for the Islamic Domain Leveraging Multiprocessing Design in Rust","date":"2024-11-09","arxiv_id":"2411.06151","repositories_listed":0,"syntology":null},{"url":null,"slug":"cross-domain-transfer-learning-using","title":"Cross-Domain Transfer Learning using Attention Latent Features for Multi-Agent Trajectory Prediction","date":"2024-11-09","arxiv_id":"2411.06087","repositories_listed":0,"syntology":null},{"url":null,"slug":"curriculum-learning-for-few-shot-domain","title":"Curriculum Learning for Few-Shot Domain Adaptation in CT-based Airway Tree Segmentation","date":"2024-11-08","arxiv_id":"2411.05779","repositories_listed":0,"syntology":null},{"url":null,"slug":"supporting-automated-fact-checking-across","title":"Supporting Automated Fact-checking across Topics: Similarity-driven Gradual Topic Learning for Claim Detection","date":"2024-11-08","arxiv_id":"2411.05460","repositories_listed":0,"syntology":null},{"url":null,"slug":"anticipatory-understanding-of-resilient","title":"Anticipatory Understanding of Resilient Agriculture to Climate","date":"2024-11-07","arxiv_id":"2411.05219","repositories_listed":0,"syntology":null},{"url":null,"slug":"controlling-human-shape-and-pose-in-text-to","title":"Controlling Human Shape and Pose in Text-to-Image Diffusion Models via Domain Adaptation","date":"2024-11-07","arxiv_id":"2411.04724","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-bronchoscopy-depth-estimation","title":"Enhancing Bronchoscopy Depth Estimation through Synthetic-to-Real Domain Adaptation","date":"2024-11-07","arxiv_id":"2411.04404","repositories_listed":0,"syntology":null},{"url":null,"slug":"from-electrode-to-global-brain-integrating","title":"From Electrode to Global Brain: Integrating Multi- and Cross-Scale Brain Connections and Interactions Under Cross-Subject and Within-Subject Scenarios","date":"2024-11-07","arxiv_id":"2411.05862","repositories_listed":0,"syntology":null},{"url":null,"slug":"in-the-era-of-prompt-learning-with-vision","title":"In the Era of Prompt Learning with Vision-Language Models","date":"2024-11-07","arxiv_id":"2411.04892","repositories_listed":0,"syntology":null},{"url":null,"slug":"progressive-multi-level-alignments-for-semi","title":"Progressive Multi-Level Alignments for Semi-Supervised Domain Adaptation SAR Target Recognition Using Simulated Data","date":"2024-11-07","arxiv_id":"2411.04711","repositories_listed":0,"syntology":null},{"url":null,"slug":"zero-shot-temporal-resolution-domain","title":"Zero-Shot Temporal Resolution Domain Adaptation for Spiking Neural Networks","date":"2024-11-07","arxiv_id":"2411.04760","repositories_listed":0,"syntology":null},{"url":null,"slug":"from-pixels-to-prose-advancing-multi-modal","title":"From Pixels to Prose: Advancing Multi-Modal Language Models for Remote Sensing","date":"2024-11-05","arxiv_id":"2411.05826","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-modal-nerf-self-supervision-for-lidar","title":"Multi-modal NeRF Self-Supervision for LiDAR Semantic Segmentation","date":"2024-11-05","arxiv_id":"2411.02969","repositories_listed":0,"syntology":null},{"url":null,"slug":"personalized-continual-eeg-decoding-framework","title":"Personalized Continual EEG Decoding: Retaining and Transferring Knowledge","date":"2024-11-04","arxiv_id":"2411.11874","repositories_listed":0,"syntology":null},{"url":null,"slug":"weakly-supervised-deep-learning-model-with","title":"Weakly supervised deep learning model with size constraint for prostate cancer detection in multiparametric MRI and generalization to unseen domains","date":"2024-11-04","arxiv_id":"2411.02466","repositories_listed":0,"syntology":null},{"url":null,"slug":"generative-ai-based-pipeline-architecture-for","title":"Generative AI-based Pipeline Architecture for Increasing Training Efficiency in Intelligent Weed Control Systems","date":"2024-11-01","arxiv_id":"2411.00548","repositories_listed":0,"syntology":null},{"url":null,"slug":"from-web-data-to-real-fields-low-cost","title":"From Web Data to Real Fields: Low-Cost Unsupervised Domain Adaptation for Agricultural Robots","date":"2024-10-31","arxiv_id":"2410.23906","repositories_listed":0,"syntology":null},{"url":null,"slug":"schema-augmentation-for-zero-shot-domain","title":"Schema Augmentation for Zero-Shot Domain Adaptation in Dialogue State Tracking","date":"2024-10-31","arxiv_id":"2411.00150","repositories_listed":0,"syntology":null},{"url":"/paper/revisiting-multi-granularity-representation","slug":"revisiting-multi-granularity-representation","title":"Revisiting Multi-Granularity Representation via Group Contrastive Learning for Unsupervised Vehicle Re-identification","date":"2024-10-29","arxiv_id":"2410.21667","repositories_listed":0,"syntology":null},{"url":null,"slug":"unified-domain-generalization-and-adaptation","title":"Unified Domain Generalization and Adaptation for Multi-View 3D Object Detection","date":"2024-10-29","arxiv_id":"2410.22461","repositories_listed":0,"syntology":null},{"url":null,"slug":"estimating-causal-effects-of-text","title":"Estimating Causal Effects of Text Interventions Leveraging LLMs","date":"2024-10-28","arxiv_id":"2410.21474","repositories_listed":0,"syntology":null},{"url":null,"slug":"strada-llm-graph-llm-for-traffic-prediction","title":"Strada-LLM: Graph LLM for traffic prediction","date":"2024-10-28","arxiv_id":"2410.20856","repositories_listed":0,"syntology":null},{"url":null,"slug":"spdim-source-free-unsupervised-conditional","title":"SPDIM: Source-Free Unsupervised Conditional and Label Shift Adaptation in EEG","date":"2024-10-26","arxiv_id":"2411.07249","repositories_listed":0,"syntology":null},{"url":null,"slug":"resolving-domain-shift-for-representations-of","title":"Resolving Domain Shift For Representations Of Speech In Non-Invasive Brain Recordings","date":"2024-10-25","arxiv_id":"2410.19986","repositories_listed":0,"syntology":null},{"url":null,"slug":"adversarial-domain-adaptation-for-metal","title":"Adversarial Domain Adaptation for Metal Cutting Sound Detection: Leveraging Abundant Lab Data for Scarce Industry Data","date":"2024-10-23","arxiv_id":"2410.17574","repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-the-domain-adaptation-of-retrieval","title":"Leveraging the Domain Adaptation of Retrieval Augmented Generation Models for Question Answering and Reducing Hallucination","date":"2024-10-23","arxiv_id":"2410.17783","repositories_listed":0,"syntology":null},{"url":null,"slug":"simrag-self-improving-retrieval-augmented","title":"SimRAG: Self-Improving Retrieval-Augmented Generation for Adapting Large Language Models to Specialized Domains","date":"2024-10-23","arxiv_id":"2410.17952","repositories_listed":0,"syntology":null},{"url":null,"slug":"time-and-frequency-synergy-for-source-free","title":"Time and Frequency Synergy for Source-Free Time-Series Domain Adaptations","date":"2024-10-23","arxiv_id":"2410.17511","repositories_listed":0,"syntology":null},{"url":null,"slug":"together-we-can-multilingual-automatic-post","title":"Together We Can: Multilingual Automatic Post-Editing for Low-Resource Languages","date":"2024-10-23","arxiv_id":"2410.17973","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-domain-adaptation-for-action","title":"Unsupervised Domain Adaptation for Action Recognition via Self-Ensembling and Conditional Embedding Alignment","date":"2024-10-23","arxiv_id":"2410.17489","repositories_listed":0,"syntology":null},{"url":null,"slug":"zip-fit-embedding-free-data-selection-via","title":"ZIP-FIT: Embedding-Free Data Selection via Compression-Based Alignment","date":"2024-10-23","arxiv_id":"2410.18194","repositories_listed":0,"syntology":null},{"url":null,"slug":"assessment-of-transformer-based-encoder","title":"Assessment of Transformer-Based Encoder-Decoder Model for Human-Like Summarization","date":"2024-10-22","arxiv_id":"2410.16842","repositories_listed":0,"syntology":null},{"url":null,"slug":"interactive-residual-domain-adaptation","title":"Co-training partial domain adaptation networks for industrial Fault Diagnosis","date":"2024-10-22","arxiv_id":"2410.16737","repositories_listed":0,"syntology":null},{"url":null,"slug":"prototype-and-instance-contrastive-learning","title":"Prototype and Instance Contrastive Learning for Unsupervised Domain Adaptation in Speaker Verification","date":"2024-10-22","arxiv_id":"2410.17033","repositories_listed":0,"syntology":null},{"url":null,"slug":"data-efficient-clip-powered-dual-branch","title":"Data-Efficient CLIP-Powered Dual-Branch Networks for Source-Free Unsupervised Domain Adaptation","date":"2024-10-21","arxiv_id":"2410.15811","repositories_listed":0,"syntology":null},{"url":null,"slug":"domain-adaptive-neural-posterior-estimation","title":"Domain-Adaptive Neural Posterior Estimation for Strong Gravitational Lens Analysis","date":"2024-10-21","arxiv_id":"2410.16347","repositories_listed":0,"syntology":null},{"url":null,"slug":"statistical-inference-for-feature-selection","title":"Statistical Inference for Feature Selection after Optimal Transport-based Domain Adaptation","date":"2024-10-19","arxiv_id":"2410.15022","repositories_listed":0,"syntology":null},{"url":null,"slug":"ac-mix-self-supervised-adaptation-for-low","title":"AC-Mix: Self-Supervised Adaptation for Low-Resource Automatic Speech Recognition using Agnostic Contrastive Mixup","date":"2024-10-18","arxiv_id":"2410.14910","repositories_listed":0,"syntology":null},{"url":null,"slug":"pseudo-label-refinement-for-improving-self","title":"Pseudo-label Refinement for Improving Self-Supervised Learning Systems","date":"2024-10-18","arxiv_id":"2410.14242","repositories_listed":0,"syntology":null},{"url":null,"slug":"day-night-adaptation-an-innovative-source","title":"Day-Night Adaptation: An Innovative Source-free Adaptation Framework for Medical Image Segmentation","date":"2024-10-17","arxiv_id":"2410.13472","repositories_listed":0,"syntology":null},{"url":null,"slug":"gradual-domain-adaptation-via-manifold","title":"Gradual Domain Adaptation via Manifold-Constrained Distributionally Robust Optimization","date":"2024-10-17","arxiv_id":"2410.14061","repositories_listed":0,"syntology":null},{"url":null,"slug":"dual-action-policy-for-robust-sim-to-real","title":"Dual Action Policy for Robust Sim-to-Real Reinforcement Learning","date":"2024-10-16","arxiv_id":"2410.12250","repositories_listed":0,"syntology":null},{"url":null,"slug":"ifuzzytl-interpretable-fuzzy-transfer","title":"iFuzzyTL: Interpretable Fuzzy Transfer Learning for SSVEP BCI System","date":"2024-10-16","arxiv_id":"2410.12267","repositories_listed":0,"syntology":null}],"record_sha256":"172df9c3dc45c593011d49af95a856ae4f182be2aa4c383e01b53de52fffa74c","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}