{"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/adam/papers/15","list_of":"/method/adam","method":"Adam","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":15,"pages_in_order":244,"rows_per_page":100,"rows":[1401,1500],"of":24390,"counts":{"archive_papers_tagged":24390,"with_a_code_link":10944,"where_syntology_ran_a_sample":3424,"not_listed_spam_title":0,"listed":24390,"listed_where_code_ran":3424,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":2899,"every_run_a_failure_of_syntologys_instrument":525,"listed_with_a_run_with_no_instrument_failure":2899,"listed_every_run_a_failure_of_syntologys_instrument":525,"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/adam","prev":"/method/adam/papers/14","next":"/method/adam/papers/16","papers":[{"paper":"/paper/leveraging-large-language-models-to-address","slug":"leveraging-large-language-models-to-address","title":"Leveraging Large Language Models to Address Data Scarcity in Machine Learning: Applications in Graphene Synthesis","date":"2025-03-06","arxiv_id":"2503.04870","n_code_links":1,"syntology":null},{"paper":"/paper/toward-lightweight-and-fast-decoders-for","slug":"toward-lightweight-and-fast-decoders-for","title":"Toward Lightweight and Fast Decoders for Diffusion Models in Image and Video Generation","date":"2025-03-06","arxiv_id":"2503.04871","n_code_links":1,"syntology":null},{"paper":null,"slug":"towards-autonomous-reinforcement-learning-for","title":"Towards Autonomous Reinforcement Learning for Real-World Robotic Manipulation with Large Language Models","date":"2025-03-06","arxiv_id":"2503.04280","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-multimodal-framework-for-topic-propagation","title":"A Multimodal Framework for Topic Propagation Classification in Social Networks","date":"2025-03-05","arxiv_id":"2503.03112","n_code_links":0,"syntology":null},{"paper":"/paper/all-atom-diffusion-transformers-unified","slug":"all-atom-diffusion-transformers-unified","title":"All-atom Diffusion Transformers: Unified generative modelling of molecules and materials","date":"2025-03-05","arxiv_id":"2503.03965","n_code_links":1,"syntology":{"ran":6,"of":7,"n_ran_checked":5,"n_instrument":1,"unverified":1,"pointer_only":7,"phrase":"6 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; 1 where Syntology's instrument failed) · 1 unverified","official":{"repos":["facebookresearch/all-atom-diffusion-transformer"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/can-frontier-llms-replace-annotators-in","slug":"can-frontier-llms-replace-annotators-in","title":"Can Frontier LLMs Replace Annotators in Biomedical Text Mining? Analyzing Challenges and Exploring Solutions","date":"2025-03-05","arxiv_id":"2503.03261","n_code_links":1,"syntology":null},{"paper":null,"slug":"dtu-net-a-multi-scale-dilated-transformer","title":"DTU-Net: A Multi-Scale Dilated Transformer Network for Nonlinear Hyperspectral Unmixing","date":"2025-03-05","arxiv_id":"2503.03465","n_code_links":0,"syntology":null},{"paper":"/paper/full-dof-egomotion-estimation-for-event","slug":"full-dof-egomotion-estimation-for-event","title":"Full-DoF Egomotion Estimation for Event Cameras Using Geometric Solvers","date":"2025-03-05","arxiv_id":"2503.03307","n_code_links":1,"syntology":null},{"paper":null,"slug":"intermediate-task-transfer-learning","title":"Intermediate-Task Transfer Learning: Leveraging Sarcasm Detection for Stance Detection","date":"2025-03-05","arxiv_id":"2503.03172","n_code_links":0,"syntology":null},{"paper":null,"slug":"large-language-models-in-finance-estimating","title":"Large language models in finance : what is financial sentiment?","date":"2025-03-05","arxiv_id":"2503.03612","n_code_links":0,"syntology":null},{"paper":"/paper/ma-lot-multi-agent-lean-based-long-chain-of","slug":"ma-lot-multi-agent-lean-based-long-chain-of","title":"MA-LoT: Multi-Agent Lean-based Long Chain-of-Thought Reasoning enhances Formal Theorem Proving","date":"2025-03-05","arxiv_id":"2503.03205","n_code_links":1,"syntology":null},{"paper":null,"slug":"on-the-convergence-of-adam-type-algorithm-for","title":"On the Convergence of Adam-Type Algorithm for Bilevel Optimization under Unbounded Smoothness","date":"2025-03-05","arxiv_id":"2503.03908","n_code_links":0,"syntology":null},{"paper":null,"slug":"pathrwkv-enabling-whole-slide-prediction-with","title":"PathRWKV: Enabling Whole Slide Prediction with Recurrent-Transformer","date":"2025-03-05","arxiv_id":"2503.03199","n_code_links":0,"syntology":null},{"paper":null,"slug":"personalized-federated-fine-tuning-for","title":"Personalized Federated Fine-tuning for Heterogeneous Data: An Automatic Rank Learning Approach via Two-Level LoRA","date":"2025-03-05","arxiv_id":"2503.03920","n_code_links":0,"syntology":null},{"paper":null,"slug":"pretrained-llms-as-real-time-controllers-for","title":"Pretrained LLMs as Real-Time Controllers for Robot Operated Serial Production Line","date":"2025-03-05","arxiv_id":"2503.03889","n_code_links":0,"syntology":null},{"paper":null,"slug":"riskagent-autonomous-medical-ai-copilot-for","title":"RiskAgent: Autonomous Medical AI Copilot for Generalist Risk Prediction","date":"2025-03-05","arxiv_id":"2503.03802","n_code_links":0,"syntology":null},{"paper":null,"slug":"sarcasm-detection-as-a-catalyst-improving","title":"Sarcasm Detection as a Catalyst: Improving Stance Detection with Cross-Target Capabilities","date":"2025-03-05","arxiv_id":"2503.03787","n_code_links":0,"syntology":null},{"paper":"/paper/scalefusionnet-transformer-guided-multi-scale","slug":"scalefusionnet-transformer-guided-multi-scale","title":"ScaleFusionNet: Transformer-Guided Multi-Scale Feature Fusion for Skin Lesion Segmentation","date":"2025-03-05","arxiv_id":"2503.03327","n_code_links":1,"syntology":null},{"paper":"/paper/the-box-is-in-the-pen-evaluating-commonsense-1","slug":"the-box-is-in-the-pen-evaluating-commonsense-1","title":"The Box is in the Pen: Evaluating Commonsense Reasoning in Neural Machine Translation","date":"2025-03-05","arxiv_id":"2503.03308","n_code_links":1,"syntology":null},{"paper":"/paper/bhvit-binarized-hybrid-vision-transformer","slug":"bhvit-binarized-hybrid-vision-transformer","title":"BHViT: Binarized Hybrid Vision Transformer","date":"2025-03-04","arxiv_id":"2503.02394","n_code_links":1,"syntology":{"ran":16,"of":29,"n_ran_checked":15,"n_instrument":1,"unverified":13,"pointer_only":0,"phrase":"16 ran (of which 13 constructed an object rather than computing a result; 15 with no instrument failure: 0 honoured, 0 violated, 15 with no contract checked; 1 where Syntology's instrument failed) · 13 unverified","official":{"repos":["IMRL/BHViT"],"state":"official (archive's flag): 16 ran","n_ran":16,"n_constructed":13,"n_ran_no_instrument_failure":15,"n_unverified":13,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"closing-the-intent-to-reality-gap-via","title":"Closing the Intent-to-Behavior Gap via Fulfillment Priority Logic","date":"2025-03-04","arxiv_id":"2503.05818","n_code_links":0,"syntology":null},{"paper":null,"slug":"coserve-efficient-collaboration-of-experts","title":"CoServe: Efficient Collaboration-of-Experts (CoE) Model Inference with Limited Memory","date":"2025-03-04","arxiv_id":"2503.02354","n_code_links":0,"syntology":null},{"paper":null,"slug":"developing-a-pet-ct-foundation-model-for","title":"Developing a PET/CT Foundation Model for Cross-Modal Anatomical and Functional Imaging","date":"2025-03-04","arxiv_id":"2503.02824","n_code_links":0,"syntology":null},{"paper":null,"slug":"effectively-steer-llm-to-follow-preference","title":"Effectively Steer LLM To Follow Preference via Building Confident Directions","date":"2025-03-04","arxiv_id":"2503.02989","n_code_links":0,"syntology":null},{"paper":null,"slug":"fouriernat-a-fourier-mixing-based-non","title":"FourierNAT: A Fourier-Mixing-Based Non-Autoregressive Transformer for Parallel Sequence Generation","date":"2025-03-04","arxiv_id":"2503.07630","n_code_links":0,"syntology":null},{"paper":"/paper/graph-transformer-with-disease-subgraph","slug":"graph-transformer-with-disease-subgraph","title":"Graph Transformer with Disease Subgraph Positional Encoding for Improved Comorbidity Prediction","date":"2025-03-04","arxiv_id":"2503.03046","n_code_links":1,"syntology":null},{"paper":null,"slug":"interpretable-few-shot-retinal-disease","title":"Interpretable Few-Shot Retinal Disease Diagnosis with Concept-Guided Prompting of Vision-Language Models","date":"2025-03-04","arxiv_id":"2503.02917","n_code_links":0,"syntology":null},{"paper":null,"slug":"learning-precoding-in-multi-user-multi","title":"Learning Precoding in Multi-user Multi-antenna Systems: Transformer or Graph Transformer?","date":"2025-03-04","arxiv_id":"2503.02998","n_code_links":0,"syntology":null},{"paper":null,"slug":"llave-large-language-and-vision-embedding","title":"LLaVE: Large Language and Vision Embedding Models with Hardness-Weighted Contrastive Learning","date":"2025-03-04","arxiv_id":"2503.04812","n_code_links":0,"syntology":null},{"paper":null,"slug":"network-traffic-classification-using-machine","title":"Network Traffic Classification Using Machine Learning, Transformer, and Large Language Models","date":"2025-03-04","arxiv_id":"2503.02141","n_code_links":0,"syntology":null},{"paper":null,"slug":"optimizing-open-domain-question-answering","title":"Optimizing open-domain question answering with graph-based retrieval augmented generation","date":"2025-03-04","arxiv_id":"2503.02922","n_code_links":0,"syntology":null},{"paper":null,"slug":"pennylang-pioneering-llm-based-quantum-code","title":"PennyLang: Pioneering LLM-Based Quantum Code Generation with a Novel PennyLane-Centric Dataset","date":"2025-03-04","arxiv_id":"2503.02497","n_code_links":0,"syntology":null},{"paper":null,"slug":"remote-sensing-image-classification-using-1","title":"Remote Sensing Image Classification Using Convolutional Neural Network (CNN) and Transfer Learning Techniques","date":"2025-03-04","arxiv_id":"2503.02510","n_code_links":0,"syntology":null},{"paper":null,"slug":"tabby-tabular-data-synthesis-with-language","title":"Tabby: Tabular Data Synthesis with Language Models","date":"2025-03-04","arxiv_id":"2503.02152","n_code_links":0,"syntology":null},{"paper":null,"slug":"target-return-optimizer-for-multi-game","title":"Target Return Optimizer for Multi-Game Decision Transformer","date":"2025-03-04","arxiv_id":"2503.02311","n_code_links":0,"syntology":null},{"paper":null,"slug":"tetra-vpr-a-ternary-transformer-approach-for","title":"TeTRA-VPR: A Ternary Transformer Approach for Compact Visual Place Recognition","date":"2025-03-04","arxiv_id":"2503.02511","n_code_links":0,"syntology":null},{"paper":null,"slug":"use-me-wisely-ai-driven-assessment-for-llm","title":"Use Me Wisely: AI-Driven Assessment for LLM Prompting Skills Development","date":"2025-03-04","arxiv_id":"2503.02532","n_code_links":0,"syntology":null},{"paper":null,"slug":"weak-to-strong-generalization-even-in-random","title":"Weak-to-Strong Generalization Even in Random Feature Networks, Provably","date":"2025-03-04","arxiv_id":"2503.02877","n_code_links":0,"syntology":null},{"paper":"/paper/wikipedia-in-the-era-of-llms-evolution-and","slug":"wikipedia-in-the-era-of-llms-evolution-and","title":"Wikipedia in the Era of LLMs: Evolution and Risks","date":"2025-03-04","arxiv_id":"2503.02879","n_code_links":1,"syntology":null},{"paper":"/paper/wyckoff-transformer-generation-of-symmetric","slug":"wyckoff-transformer-generation-of-symmetric","title":"Wyckoff Transformer: Generation of Symmetric Crystals","date":"2025-03-04","arxiv_id":"2503.02407","n_code_links":1,"syntology":null},{"paper":null,"slug":"zero-shot-multi-label-classification-of","title":"Zero-Shot Multi-Label Classification of Bangla Documents: Large Decoders Vs. Classic Encoders","date":"2025-03-04","arxiv_id":"2503.02993","n_code_links":0,"syntology":null},{"paper":"/paper/2503-01306","slug":"2503-01306","title":"From Claims to Evidence: A Unified Framework and Critical Analysis of CNN vs. Transformer vs. Mamba in Medical Image Segmentation","date":"2025-03-03","arxiv_id":"2503.01306","n_code_links":1,"syntology":null},{"paper":null,"slug":"2503-01394","title":"Enhancing Social Media Rumor Detection: A Semantic and Graph Neural Network Approach for the 2024 Global Election","date":"2025-03-03","arxiv_id":"2503.01394","n_code_links":0,"syntology":null},{"paper":null,"slug":"2503-01458","title":"SrSv: Integrating Sequential Rollouts with Sequential Value Estimation for Multi-agent Reinforcement Learning","date":"2025-03-03","arxiv_id":"2503.01458","n_code_links":0,"syntology":null},{"paper":null,"slug":"2503-01592","title":"An Efficient Approach to Detecting Lung Nodules Using Swin Transformer","date":"2025-03-03","arxiv_id":"2503.01592","n_code_links":0,"syntology":null},{"paper":null,"slug":"2503-01630","title":"Machine Learners Should Acknowledge the Legal Implications of Large Language Models as Personal Data","date":"2025-03-03","arxiv_id":"2503.01630","n_code_links":0,"syntology":null},{"paper":null,"slug":"2503-01713","title":"SAGE: A Framework of Precise Retrieval for RAG","date":"2025-03-03","arxiv_id":"2503.01713","n_code_links":0,"syntology":null},{"paper":null,"slug":"2503-01814","title":"LLMInit: A Free Lunch from Large Language Models for Selective Initialization of Recommendation","date":"2025-03-03","arxiv_id":"2503.01814","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-hybrid-cnn-transformer-model-for-heart","title":"A Hybrid CNN-Transformer Model for Heart Disease Prediction Using Life History Data","date":"2025-03-03","arxiv_id":"2503.02124","n_code_links":0,"syntology":null},{"paper":"/paper/architectural-and-inferential-inductive","slug":"architectural-and-inferential-inductive","title":"Architectural and Inferential Inductive Biases For Exchangeable Sequence Modeling","date":"2025-03-03","arxiv_id":"2503.01215","n_code_links":1,"syntology":null},{"paper":null,"slug":"asktoact-enhancing-llms-tool-use-via-self","title":"AskToAct: Enhancing LLMs Tool Use via Self-Correcting Clarification","date":"2025-03-03","arxiv_id":"2503.01940","n_code_links":0,"syntology":null},{"paper":null,"slug":"attention-condensation-via-sparsity-induced","title":"Attention Condensation via Sparsity Induced Regularized Training","date":"2025-03-03","arxiv_id":"2503.01564","n_code_links":0,"syntology":null},{"paper":null,"slug":"boolean-aware-attention-for-dense-retrieval","title":"Boolean-aware Attention for Dense Retrieval","date":"2025-03-03","arxiv_id":"2503.01753","n_code_links":0,"syntology":null},{"paper":"/paper/cancer-type-stage-and-prognosis-assessment","slug":"cancer-type-stage-and-prognosis-assessment","title":"Cancer Type, Stage and Prognosis Assessment from Pathology Reports using LLMs","date":"2025-03-03","arxiv_id":"2503.01194","n_code_links":1,"syntology":null},{"paper":null,"slug":"dementia-insights-a-context-based-multimodal","title":"Dementia Insights: A Context-Based MultiModal Approach","date":"2025-03-03","arxiv_id":"2503.01226","n_code_links":0,"syntology":null},{"paper":null,"slug":"efficient-or-powerful-trade-offs-between","title":"Efficient or Powerful? Trade-offs Between Machine Learning and Deep Learning for Mental Illness Detection on Social Media","date":"2025-03-03","arxiv_id":"2503.01082","n_code_links":0,"syntology":null},{"paper":"/paper/forgetting-transformer-softmax-attention-with","slug":"forgetting-transformer-softmax-attention-with","title":"Forgetting Transformer: Softmax Attention with a Forget Gate","date":"2025-03-03","arxiv_id":"2503.02130","n_code_links":1,"syntology":{"ran":11,"of":13,"n_ran_checked":9,"n_instrument":2,"unverified":2,"pointer_only":0,"phrase":"11 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 0 violated, 9 with no contract checked; 2 where Syntology's instrument failed) · 2 unverified","official":{"repos":["zhixuan-lin/forgetting-transformer"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"hierarchical-causal-transformer-with","title":"HeterRec: Heterogeneous Information Transformer for Scalable Sequential Recommendation","date":"2025-03-03","arxiv_id":"2503.01469","n_code_links":0,"syntology":null},{"paper":"/paper/hoh-a-dynamic-benchmark-for-evaluating-the","slug":"hoh-a-dynamic-benchmark-for-evaluating-the","title":"HoH: A Dynamic Benchmark for Evaluating the Impact of Outdated Information on Retrieval-Augmented Generation","date":"2025-03-03","arxiv_id":"2503.04800","n_code_links":0,"syntology":{"ran":3,"of":3,"n_ran_checked":3,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":null}},{"paper":"/paper/how-simple-can-you-go-an-off-the-shelf","slug":"how-simple-can-you-go-an-off-the-shelf","title":"How simple can you go? An off-the-shelf transformer approach to molecular dynamics","date":"2025-03-03","arxiv_id":"2503.01431","n_code_links":1,"syntology":null},{"paper":"/paper/interactive-gadolinium-free-mri-synthesis-a","slug":"interactive-gadolinium-free-mri-synthesis-a","title":"Interactive Gadolinium-Free MRI Synthesis: A Transformer with Localization Prompt Learning","date":"2025-03-03","arxiv_id":"2503.01265","n_code_links":1,"syntology":null},{"paper":null,"slug":"meshpad-interactive-sketch-conditioned","title":"MeshPad: Interactive Sketch-Conditioned Artist-Designed Mesh Generation and Editing","date":"2025-03-03","arxiv_id":"2503.01425","n_code_links":0,"syntology":null},{"paper":null,"slug":"non-convergence-to-the-optimal-risk-for-adam","title":"Non-convergence to the optimal risk for Adam and stochastic gradient descent optimization in the training of deep neural networks","date":"2025-03-03","arxiv_id":"2503.01660","n_code_links":0,"syntology":null},{"paper":null,"slug":"primus-enforcing-attention-usage-for-3d","title":"Primus: Enforcing Attention Usage for 3D Medical Image Segmentation","date":"2025-03-03","arxiv_id":"2503.01835","n_code_links":0,"syntology":null},{"paper":"/paper/retrieval-augmented-perception-high","slug":"retrieval-augmented-perception-high","title":"Retrieval-Augmented Perception: High-Resolution Image Perception Meets Visual RAG","date":"2025-03-03","arxiv_id":"2503.01222","n_code_links":1,"syntology":null},{"paper":"/paper/seper-measure-retrieval-utility-through-the","slug":"seper-measure-retrieval-utility-through-the","title":"SePer: Measure Retrieval Utility Through The Lens Of Semantic Perplexity Reduction","date":"2025-03-03","arxiv_id":"2503.01478","n_code_links":1,"syntology":{"ran":2,"of":4,"n_ran_checked":1,"n_instrument":1,"unverified":2,"pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","official":{"repos":["sepermetric/seper"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"srag-structured-retrieval-augmented","title":"SRAG: Structured Retrieval-Augmented Generation for Multi-Entity Question Answering over Wikipedia Graph","date":"2025-03-03","arxiv_id":"2503.01346","n_code_links":0,"syntology":null},{"paper":null,"slug":"streaming-piano-transcription-based-on","title":"Streaming Piano Transcription Based on Consistent Onset and Offset Decoding with Sustain Pedal Detection","date":"2025-03-03","arxiv_id":"2503.01362","n_code_links":0,"syntology":null},{"paper":null,"slug":"syntactic-learnability-of-echo-state-neural","title":"Syntactic Learnability of Echo State Neural Language Models at Scale","date":"2025-03-03","arxiv_id":"2503.01724","n_code_links":0,"syntology":null},{"paper":null,"slug":"unify-and-anchor-a-context-aware-transformer","title":"Unify and Anchor: A Context-Aware Transformer for Cross-Domain Time Series Forecasting","date":"2025-03-03","arxiv_id":"2503.01157","n_code_links":0,"syntology":null},{"paper":null,"slug":"using-not-so-large-language-models-for","title":"Using (Not so) Large Language Models for Generating Simulation Models in a Formal DSL -- A Study on Reaction Networks","date":"2025-03-03","arxiv_id":"2503.01675","n_code_links":0,"syntology":null},{"paper":null,"slug":"vikanformer-embedding-kolmogorov-arnold","title":"ViKANformer: Embedding Kolmogorov Arnold Networks in Vision Transformers for Pattern-Based Learning","date":"2025-03-03","arxiv_id":"2503.01124","n_code_links":0,"syntology":null},{"paper":"/paper/when-can-you-get-away-with-low-memory-adam","slug":"when-can-you-get-away-with-low-memory-adam","title":"When Can You Get Away with Low Memory Adam?","date":"2025-03-03","arxiv_id":"2503.01843","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["dayal-kalra/low-memory-adam"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/2503-00955","slug":"2503-00955","title":"SemViQA: A Semantic Question Answering System for Vietnamese Information Fact-Checking","date":"2025-03-02","arxiv_id":"2503.00955","n_code_links":1,"syntology":null},{"paper":null,"slug":"er-rag-enhance-rag-with-er-based-unified","title":"ER-RAG: Enhance RAG with ER-Based Unified Modeling of Heterogeneous Data Sources","date":"2025-03-02","arxiv_id":"2504.06271","n_code_links":0,"syntology":null},{"paper":null,"slug":"optimizing-multi-hop-document-retrieval","title":"Optimizing Multi-Hop Document Retrieval Through Intermediate Representations","date":"2025-03-02","arxiv_id":"2503.04796","n_code_links":0,"syntology":null},{"paper":"/paper/training-free-dataset-pruning-for-instance","slug":"training-free-dataset-pruning-for-instance","title":"Training-Free Dataset Pruning for Instance Segmentation","date":"2025-03-02","arxiv_id":"2503.00828","n_code_links":1,"syntology":{"ran":5,"of":8,"n_ran_checked":1,"n_instrument":4,"unverified":3,"pointer_only":8,"phrase":"5 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; 4 where Syntology's instrument failed) · 3 unverified","official":{"repos":["he-y/dataset-pruning-for-instance-segmentation"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"unmasking-digital-falsehoods-a-comparative","title":"Unmasking Digital Falsehoods: A Comparative Analysis of LLM-Based Misinformation Detection Strategies","date":"2025-03-02","arxiv_id":"2503.00724","n_code_links":0,"syntology":null},{"paper":null,"slug":"2503-00309","title":"Pseudo-Knowledge Graph: Meta-Path Guided Retrieval and In-Graph Text for RAG-Equipped LLM","date":"2025-03-01","arxiv_id":"2503.00309","n_code_links":0,"syntology":null},{"paper":"/paper/2503-00455","slug":"2503-00455","title":"PodAgent: A Comprehensive Framework for Podcast Generation","date":"2025-03-01","arxiv_id":"2503.00455","n_code_links":1,"syntology":null},{"paper":null,"slug":"2503-00596","title":"BadJudge: Backdoor Vulnerabilities of LLM-as-a-Judge","date":"2025-03-01","arxiv_id":"2503.00596","n_code_links":0,"syntology":null},{"paper":null,"slug":"hierarchical-multi-stage-bert-fusion","title":"Hierarchical Multi-Stage BERT Fusion Framework with Dual Attention for Enhanced Cyberbullying Detection in Social Media","date":"2025-03-01","arxiv_id":"2503.00342","n_code_links":0,"syntology":null},{"paper":null,"slug":"learning-conditional-average-treatment","title":"Learning Conditional Average Treatment Effects in Regression Discontinuity Designs using Bayesian Additive Regression Trees","date":"2025-03-01","arxiv_id":"2503.00326","n_code_links":0,"syntology":null},{"paper":null,"slug":"psychological-counseling-ability-of-large","title":"Psychological Counseling Ability of Large Language Models","date":"2025-03-01","arxiv_id":"2503.07627","n_code_links":0,"syntology":null},{"paper":"/paper/u-niah-unified-rag-and-llm-evaluation-for","slug":"u-niah-unified-rag-and-llm-evaluation-for","title":"U-NIAH: Unified RAG and LLM Evaluation for Long Context Needle-In-A-Haystack","date":"2025-03-01","arxiv_id":"2503.00353","n_code_links":1,"syntology":null},{"paper":null,"slug":"using-machine-learning-for-move-sequence","title":"Using Machine Learning for move sequence visualization and generation in climbing","date":"2025-03-01","arxiv_id":"2503.00458","n_code_links":0,"syntology":null},{"paper":"/paper/2502-21309","slug":"2502-21309","title":"FANformer: Improving Large Language Models Through Effective Periodicity Modeling","date":"2025-02-28","arxiv_id":"2502.21309","n_code_links":1,"syntology":{"ran":2,"of":3,"n_ran_checked":0,"n_instrument":2,"unverified":1,"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) · 1 unverified","official":{"repos":["yihongdong/fanformer"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/2503-00211","slug":"2503-00211","title":"SafeAuto: Knowledge-Enhanced Safe Autonomous Driving with Multimodal Foundation Models","date":"2025-02-28","arxiv_id":"2503.00211","n_code_links":1,"syntology":null},{"paper":"/paper/a-novel-fourier-adjacency-transformer-for","slug":"a-novel-fourier-adjacency-transformer-for","title":"A novel Fourier Adjacency Transformer for advanced EEG emotion recognition","date":"2025-02-28","arxiv_id":"2503.13465","n_code_links":1,"syntology":{"ran":11,"of":14,"n_ran_checked":11,"n_instrument":0,"unverified":3,"pointer_only":0,"phrase":"11 ran (of which 0 constructed an object rather than computing a result; 11 with no instrument failure: 1 honoured, 0 violated, 10 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","official":{"repos":["YanhaoHuang23/FAT"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":11,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"beyond-words-a-latent-memory-approach-to","title":"Beyond Words: A Latent Memory Approach to Internal Reasoning in LLMs","date":"2025-02-28","arxiv_id":"2502.21030","n_code_links":0,"syntology":null},{"paper":"/paper/bst-badminton-stroke-type-transformer-for","slug":"bst-badminton-stroke-type-transformer-for","title":"BST: Badminton Stroke-type Transformer for Skeleton-based Action Recognition in Racket Sports","date":"2025-02-28","arxiv_id":"2502.21085","n_code_links":1,"syntology":null},{"paper":"/paper/codi-compressing-chain-of-thought-into","slug":"codi-compressing-chain-of-thought-into","title":"CODI: Compressing Chain-of-Thought into Continuous Space via Self-Distillation","date":"2025-02-28","arxiv_id":"2502.21074","n_code_links":1,"syntology":{"ran":0,"of":2,"n_ran_checked":0,"n_instrument":0,"unverified":2,"pointer_only":2,"phrase":"0 ran · 2 unverified","official":null}},{"paper":null,"slug":"ext2gen-alignment-through-unified-extraction","title":"Ext2Gen: Alignment through Unified Extraction and Generation for Robust Retrieval-Augmented Generation","date":"2025-02-28","arxiv_id":"2503.04789","n_code_links":0,"syntology":null},{"paper":"/paper/faster-focal-token-acquiring-and-scaling","slug":"faster-focal-token-acquiring-and-scaling","title":"FASTer: Focal Token Acquiring-and-Scaling Transformer for Long-term 3D Object Detection","date":"2025-02-28","arxiv_id":"2503.01899","n_code_links":1,"syntology":null},{"paper":"/paper/jitter-jigsaw-temporal-transformer-for-event","slug":"jitter-jigsaw-temporal-transformer-for-event","title":"JiTTER: Jigsaw Temporal Transformer for Event Reconstruction for Self-Supervised Sound Event Detection","date":"2025-02-28","arxiv_id":"2502.20857","n_code_links":1,"syntology":null},{"paper":"/paper/lexrag-benchmarking-retrieval-augmented","slug":"lexrag-benchmarking-retrieval-augmented","title":"LexRAG: Benchmarking Retrieval-Augmented Generation in Multi-Turn Legal Consultation Conversation","date":"2025-02-28","arxiv_id":"2502.20640","n_code_links":1,"syntology":null},{"paper":"/paper/nutrigen-personalized-meal-plan-generator","slug":"nutrigen-personalized-meal-plan-generator","title":"NutriGen: Personalized Meal Plan Generator Leveraging Large Language Models to Enhance Dietary and Nutritional Adherence","date":"2025-02-28","arxiv_id":"2502.20601","n_code_links":1,"syntology":null},{"paper":null,"slug":"retrieval-augmented-generation-for-topic","title":"Retrieval Augmented Generation for Topic Modeling in Organizational Research: An Introduction with Empirical Demonstration","date":"2025-02-28","arxiv_id":"2502.20963","n_code_links":0,"syntology":null},{"paper":"/paper/ruccod-towards-automated-icd-coding-in","slug":"ruccod-towards-automated-icd-coding-in","title":"RuCCoD: Towards Automated ICD Coding in Russian","date":"2025-02-28","arxiv_id":"2502.21263","n_code_links":1,"syntology":null},{"paper":null,"slug":"solar-multimodal-transformer-intraday-solar","title":"Solar Multimodal Transformer: Intraday Solar Irradiance Predictor using Public Cameras and Time Series","date":"2025-02-28","arxiv_id":"2503.00250","n_code_links":0,"syntology":null}],"record_sha256":"0fcaa4240edd92c8fce5547e1bcc99a775619bb145e5154f613a7532d02ce008","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}