{"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/dense-connections/papers/37","list_of":"/method/dense-connections","method":"Dense Connections","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":37,"pages_in_order":293,"rows_per_page":100,"rows":[3601,3700],"of":29230,"counts":{"archive_papers_tagged":29230,"with_a_code_link":12972,"where_syntology_ran_a_sample":3929,"not_listed_spam_title":0,"listed":29230,"listed_where_code_ran":3929,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":3303,"every_run_a_failure_of_syntologys_instrument":626,"listed_with_a_run_with_no_instrument_failure":3303,"listed_every_run_a_failure_of_syntologys_instrument":626,"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/dense-connections","prev":"/method/dense-connections/papers/36","next":"/method/dense-connections/papers/38","papers":[{"paper":null,"slug":"waterfall-transformer-for-multi-person-pose","title":"Waterfall Transformer for Multi-person Pose Estimation","date":"2024-11-28","arxiv_id":"2411.18944","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-pipeline-of-neural-symbolic-integration-to","title":"Dspy-based Neural-Symbolic Pipeline to Enhance Spatial Reasoning in LLMs","date":"2024-11-27","arxiv_id":"2411.18564","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-survey-on-cutting-edge-relation-extraction","title":"A survey on cutting-edge relation extraction techniques based on language models","date":"2024-11-27","arxiv_id":"2411.18157","n_code_links":0,"syntology":null},{"paper":"/paper/aligning-knowledge-concepts-to-whole-slide","slug":"aligning-knowledge-concepts-to-whole-slide","title":"Aligning Knowledge Concepts to Whole Slide Images for Precise Histopathology Image Analysis","date":"2024-11-27","arxiv_id":"2411.18101","n_code_links":1,"syntology":null},{"paper":null,"slug":"automated-literature-review-using-nlp","title":"Automated Literature Review Using NLP Techniques and LLM-Based Retrieval-Augmented Generation","date":"2024-11-27","arxiv_id":"2411.18583","n_code_links":0,"syntology":null},{"paper":null,"slug":"can-bidirectional-encoder-become-the-ultimate","title":"Can bidirectional encoder become the ultimate winner for downstream applications of foundation models?","date":"2024-11-27","arxiv_id":"2411.18021","n_code_links":0,"syntology":null},{"paper":null,"slug":"chatgpt-as-speechwriter-for-the-french","title":"ChatGPT as speechwriter for the French presidents","date":"2024-11-27","arxiv_id":"2411.18382","n_code_links":0,"syntology":null},{"paper":"/paper/drs-deep-question-reformulation-with","slug":"drs-deep-question-reformulation-with","title":"DRS: Deep Question Reformulation With Structured Output","date":"2024-11-27","arxiv_id":"2411.17993","n_code_links":1,"syntology":null},{"paper":"/paper/enhancing-mmdit-based-text-to-image-models","slug":"enhancing-mmdit-based-text-to-image-models","title":"Enhancing MMDiT-Based Text-to-Image Models for Similar Subject Generation","date":"2024-11-27","arxiv_id":"2411.18301","n_code_links":1,"syntology":null},{"paper":"/paper/evaluating-and-improving-the-robustness-of-1","slug":"evaluating-and-improving-the-robustness-of-1","title":"Evaluating and Improving the Robustness of Security Attack Detectors Generated by LLMs","date":"2024-11-27","arxiv_id":"2411.18216","n_code_links":1,"syntology":null},{"paper":null,"slug":"exploring-depth-information-for-detecting","title":"Exploring Depth Information for Detecting Manipulated Face Videos","date":"2024-11-27","arxiv_id":"2411.18572","n_code_links":0,"syntology":null},{"paper":null,"slug":"fine-tuning-large-language-models-for-5","title":"Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study","date":"2024-11-27","arxiv_id":"2412.00098","n_code_links":0,"syntology":null},{"paper":null,"slug":"fine-tuning-small-embeddings-for-elevated","title":"Fine-Tuning Small Embeddings for Elevated Performance","date":"2024-11-27","arxiv_id":"2411.18099","n_code_links":0,"syntology":null},{"paper":null,"slug":"haat-hybrid-attention-aggregation-transformer","title":"HAAT: Hybrid Attention Aggregation Transformer for Image Super-Resolution","date":"2024-11-27","arxiv_id":"2411.18003","n_code_links":0,"syntology":null},{"paper":null,"slug":"hdi-former-hybrid-dynamic-interaction-ann-snn","title":"HDI-Former: Hybrid Dynamic Interaction ANN-SNN Transformer for Object Detection Using Frames and Events","date":"2024-11-27","arxiv_id":"2411.18658","n_code_links":0,"syntology":null},{"paper":null,"slug":"improved-implicit-diffusion-model-with","title":"Improved implicit diffusion model with knowledge distillation to estimate the spatial distribution density of carbon stock in remote sensing imagery","date":"2024-11-27","arxiv_id":"2411.17973","n_code_links":0,"syntology":null},{"paper":null,"slug":"lightweight-gaze-estimation-model-via-fusion","title":"Lightweight Gaze Estimation Model Via Fusion Global Information","date":"2024-11-27","arxiv_id":"2411.18064","n_code_links":0,"syntology":null},{"paper":null,"slug":"mvketr-chest-ct-report-generation-with-multi","title":"MvKeTR: Chest CT Report Generation with Multi-View Perception and Knowledge Enhancement","date":"2024-11-27","arxiv_id":"2411.18309","n_code_links":0,"syntology":null},{"paper":null,"slug":"on-importance-of-code-mixed-embeddings-for","title":"On Importance of Code-Mixed Embeddings for Hate Speech Identification","date":"2024-11-27","arxiv_id":"2411.18577","n_code_links":0,"syntology":null},{"paper":"/paper/paths-a-hierarchical-transformer-for","slug":"paths-a-hierarchical-transformer-for","title":"PATHS: A Hierarchical Transformer for Efficient Whole Slide Image Analysis","date":"2024-11-27","arxiv_id":"2411.18225","n_code_links":1,"syntology":null},{"paper":null,"slug":"residual-attention-single-head-vision","title":"Residual Attention Single-Head Vision Transformer Network for Rolling Bearing Fault Diagnosis in Noisy Environments","date":"2024-11-27","arxiv_id":"2412.00085","n_code_links":0,"syntology":null},{"paper":null,"slug":"rpee-heads-a-novel-benchmark-for-pedestrian","title":"RPEE-HEADS: A Novel Benchmark for Pedestrian Head Detection in Crowd Videos","date":"2024-11-27","arxiv_id":"2411.18164","n_code_links":0,"syntology":null},{"paper":"/paper/spectral-spatial-transformer-with-active","slug":"spectral-spatial-transformer-with-active","title":"Spectral-Spatial Transformer with Active Transfer Learning for Hyperspectral Image Classification","date":"2024-11-27","arxiv_id":"2411.18115","n_code_links":1,"syntology":null},{"paper":"/paper/streamlining-prediction-in-bayesian-deep","slug":"streamlining-prediction-in-bayesian-deep","title":"Streamlining Prediction in Bayesian Deep Learning","date":"2024-11-27","arxiv_id":"2411.18425","n_code_links":1,"syntology":{"ran":8,"of":10,"n_ran_checked":8,"n_instrument":0,"unverified":2,"pointer_only":0,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","official":{"repos":["aaltoml/suq"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/the-importance-of-visual-modelling-languages","slug":"the-importance-of-visual-modelling-languages","title":"The importance of visual modelling languages in generative software engineering","date":"2024-11-27","arxiv_id":"2411.17976","n_code_links":1,"syntology":null},{"paper":"/paper/training-and-evaluating-language-models-with","slug":"training-and-evaluating-language-models-with","title":"Training and Evaluating Language Models with Template-based Data Generation","date":"2024-11-27","arxiv_id":"2411.18104","n_code_links":1,"syntology":{"ran":3,"of":4,"n_ran_checked":1,"n_instrument":2,"unverified":1,"pointer_only":4,"phrase":"3 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; 2 where Syntology's instrument failed) · 1 unverified","official":{"repos":["iiis-ai/templatemath"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/training-noise-token-pruning","slug":"training-noise-token-pruning","title":"Training Noise Token Pruning","date":"2024-11-27","arxiv_id":"2411.18092","n_code_links":1,"syntology":null},{"paper":null,"slug":"unpacking-the-individual-components-of","title":"Unpacking the Individual Components of Diffusion Policy","date":"2024-11-27","arxiv_id":"2412.00084","n_code_links":0,"syntology":null},{"paper":null,"slug":"addressing-vulnerabilities-in-ai-image","title":"Addressing Vulnerabilities in AI-Image Detection: Challenges and Proposed Solutions","date":"2024-11-26","arxiv_id":"2412.00073","n_code_links":0,"syntology":null},{"paper":null,"slug":"advancing-content-moderation-evaluating-large","title":"Advancing Content Moderation: Evaluating Large Language Models for Detecting Sensitive Content Across Text, Images, and Videos","date":"2024-11-26","arxiv_id":"2411.17123","n_code_links":0,"syntology":null},{"paper":null,"slug":"an-in-depth-investigation-of-sparse-rate","title":"An In-depth Investigation of Sparse Rate Reduction in Transformer-like Models","date":"2024-11-26","arxiv_id":"2411.17182","n_code_links":0,"syntology":null},{"paper":"/paper/bert-or-fasttext-a-comparative-analysis-of","slug":"bert-or-fasttext-a-comparative-analysis-of","title":"BERT or FastText? A Comparative Analysis of Contextual as well as Non-Contextual Embeddings","date":"2024-11-26","arxiv_id":"2411.17661","n_code_links":1,"syntology":null},{"paper":"/paper/breast-tumor-classification-using","slug":"breast-tumor-classification-using","title":"Breast Tumor Classification Using EfficientNet Deep Learning Model","date":"2024-11-26","arxiv_id":"2411.17870","n_code_links":1,"syntology":null},{"paper":null,"slug":"can-artificial-intelligence-predict-clinical","title":"Can artificial intelligence predict clinical trial outcomes?","date":"2024-11-26","arxiv_id":"2411.17595","n_code_links":0,"syntology":null},{"paper":"/paper/clover-constrained-learning-with-orthonormal","slug":"clover-constrained-learning-with-orthonormal","title":"CLOVER: Cross-Layer Orthogonal Vectors Pruning and Fine-Tuning","date":"2024-11-26","arxiv_id":"2411.17426","n_code_links":1,"syntology":null},{"paper":"/paper/distributed-sign-momentum-with-local-steps","slug":"distributed-sign-momentum-with-local-steps","title":"Distributed Sign Momentum with Local Steps for Training Transformers","date":"2024-11-26","arxiv_id":"2411.17866","n_code_links":1,"syntology":null},{"paper":"/paper/efficient-deployment-of-transformer-models-in","slug":"efficient-deployment-of-transformer-models-in","title":"Efficient Deployment of Transformer Models in Analog In-Memory Computing Hardware","date":"2024-11-26","arxiv_id":"2411.17367","n_code_links":1,"syntology":null},{"paper":null,"slug":"er2score-llm-based-explainable-and","title":"ER2Score: LLM-based Explainable and Customizable Metric for Assessing Radiology Reports with Reward-Control Loss","date":"2024-11-26","arxiv_id":"2411.17301","n_code_links":0,"syntology":null},{"paper":null,"slug":"fairness-and-performance-in-harmony-data","title":"Fairness And Performance In Harmony: Data Debiasing Is All You Need","date":"2024-11-26","arxiv_id":"2411.17374","n_code_links":0,"syntology":null},{"paper":null,"slug":"geometric-point-attention-transformer-for-3d","title":"Geometric Point Attention Transformer for 3D Shape Reassembly","date":"2024-11-26","arxiv_id":"2411.17788","n_code_links":0,"syntology":null},{"paper":null,"slug":"give-me-the-code-log-analysis-of-first-year","title":"\"Give me the code\" -- Log Analysis of First-Year CS Students' Interactions With GPT","date":"2024-11-26","arxiv_id":"2411.17855","n_code_links":0,"syntology":null},{"paper":"/paper/k2ssl-a-faster-and-better-framework-for-self","slug":"k2ssl-a-faster-and-better-framework-for-self","title":"k2SSL: A Faster and Better Framework for Self-Supervised Speech Representation Learning","date":"2024-11-26","arxiv_id":"2411.17100","n_code_links":1,"syntology":null},{"paper":"/paper/leveraging-large-language-models-and-topic","slug":"leveraging-large-language-models-and-topic","title":"Leveraging Large Language Models and Topic Modeling for Toxicity Classification","date":"2024-11-26","arxiv_id":"2411.17876","n_code_links":1,"syntology":null},{"paper":"/paper/marvel-40m-multi-level-visual-elaboration-for","slug":"marvel-40m-multi-level-visual-elaboration-for","title":"MARVEL-40M+: Multi-Level Visual Elaboration for High-Fidelity Text-to-3D Content Creation","date":"2024-11-26","arxiv_id":"2411.17945","n_code_links":2,"syntology":{"ran":2,"of":6,"n_ran_checked":2,"n_instrument":0,"unverified":4,"pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 4 unverified","official":{"repos":["SadilKhan/MARVEL-FX3D","huggingface.co/datasets/sankalpsinha77/MARVEL-40M"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":4,"ran_from_kinds":["official"]}}},{"paper":"/paper/mat-multi-range-attention-transformer-for","slug":"mat-multi-range-attention-transformer-for","title":"MAT: Multi-Range Attention Transformer for Efficient Image Super-Resolution","date":"2024-11-26","arxiv_id":"2411.17214","n_code_links":1,"syntology":{"ran":4,"of":7,"n_ran_checked":4,"n_instrument":0,"unverified":3,"pointer_only":3,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","official":{"repos":["stella-von/MAT"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":"/paper/mwformer-multi-weather-image-restoration","slug":"mwformer-multi-weather-image-restoration","title":"MWFormer: Multi-Weather Image Restoration Using Degradation-Aware Transformers","date":"2024-11-26","arxiv_id":"2411.17226","n_code_links":1,"syntology":null},{"paper":null,"slug":"on-limitations-of-llm-as-annotator-for-low","title":"On Limitations of LLM as Annotator for Low Resource Languages","date":"2024-11-26","arxiv_id":"2411.17637","n_code_links":0,"syntology":null},{"paper":null,"slug":"osformer-dual-modal-o-like-super-resolution","title":"ΩSFormer: Dual-Modal Ω-like Super-Resolution Transformer Network for Cross-scale and High-accuracy Terraced Field Vectorization Extraction","date":"2024-11-26","arxiv_id":"2411.17088","n_code_links":0,"syntology":null},{"paper":"/paper/pretrained-llm-adapted-with-lora-as-a","slug":"pretrained-llm-adapted-with-lora-as-a","title":"Pretrained LLM Adapted with LoRA as a Decision Transformer for Offline RL in Quantitative Trading","date":"2024-11-26","arxiv_id":"2411.17900","n_code_links":1,"syntology":null},{"paper":null,"slug":"push-the-limit-of-multi-modal-emotion","title":"Push the Limit of Multi-modal Emotion Recognition by Prompting LLMs with Receptive-Field-Aware Attention Weighting","date":"2024-11-26","arxiv_id":"2411.17674","n_code_links":0,"syntology":null},{"paper":"/paper/satvision-toa-a-geospatial-foundation-model","slug":"satvision-toa-a-geospatial-foundation-model","title":"SatVision-TOA: A Geospatial Foundation Model for Coarse-Resolution All-Sky Remote Sensing Imagery","date":"2024-11-26","arxiv_id":"2411.17000","n_code_links":1,"syntology":null},{"paper":null,"slug":"scalable-iterative-pruning-of-large-language","title":"Scalable iterative pruning of large language and vision models using block coordinate descent","date":"2024-11-26","arxiv_id":"2411.17796","n_code_links":0,"syntology":null},{"paper":null,"slug":"scaseg-strip-cross-attention-for-efficient","title":"SCASeg: Strip Cross-Attention for Efficient Semantic Segmentation","date":"2024-11-26","arxiv_id":"2411.17061","n_code_links":0,"syntology":null},{"paper":"/paper/ted-viton-transformer-empowered-diffusion","slug":"ted-viton-transformer-empowered-diffusion","title":"TED-VITON: Transformer-Empowered Diffusion Models for Virtual Try-On","date":"2024-11-26","arxiv_id":"2411.17017","n_code_links":1,"syntology":null},{"paper":"/paper/tinyvim-frequency-decoupling-for-tiny-hybrid","slug":"tinyvim-frequency-decoupling-for-tiny-hybrid","title":"TinyViM: Frequency Decoupling for Tiny Hybrid Vision Mamba","date":"2024-11-26","arxiv_id":"2411.17473","n_code_links":1,"syntology":null},{"paper":"/paper/what-differentiates-educational-literature-a","slug":"what-differentiates-educational-literature-a","title":"What Differentiates Educational Literature? A Multimodal Fusion Approach of Transformers and Computational Linguistics","date":"2024-11-26","arxiv_id":"2411.17593","n_code_links":0,"syntology":null},{"paper":null,"slug":"adaptive-circuit-behavior-and-generalization","title":"Adaptive Circuit Behavior and Generalization in Mechanistic Interpretability","date":"2024-11-25","arxiv_id":"2411.16105","n_code_links":0,"syntology":null},{"paper":null,"slug":"are-transformers-truly-foundational-for","title":"Are Transformers Truly Foundational for Robotics?","date":"2024-11-25","arxiv_id":"2411.16917","n_code_links":0,"syntology":null},{"paper":"/paper/atomr-atomic-operator-empowered-large","slug":"atomr-atomic-operator-empowered-large","title":"AtomR: Atomic Operator-Empowered Large Language Models for Heterogeneous Knowledge Reasoning","date":"2024-11-25","arxiv_id":"2411.16495","n_code_links":1,"syntology":{"ran":13,"of":13,"n_ran_checked":13,"n_instrument":0,"unverified":0,"pointer_only":13,"phrase":"13 ran (of which 0 constructed an object rather than computing a result; 13 with no instrument failure: 0 honoured, 0 violated, 13 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["THU-KEG/AtomR"],"state":"official (archive's flag): 13 ran","n_ran":13,"n_constructed":0,"n_ran_no_instrument_failure":13,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"can-ai-grade-your-essays-a-comparative","title":"Can AI grade your essays? A comparative analysis of large language models and teacher ratings in multidimensional essay scoring","date":"2024-11-25","arxiv_id":"2411.16337","n_code_links":0,"syntology":null},{"paper":null,"slug":"catp-llm-empowering-large-language-models-for","title":"CATP-LLM: Empowering Large Language Models for Cost-Aware Tool Planning","date":"2024-11-25","arxiv_id":"2411.16313","n_code_links":0,"syntology":null},{"paper":null,"slug":"cmavit-integrating-climate-managment-and","title":"CMAViT: Integrating Climate, Managment, and Remote Sensing Data for Crop Yield Estimation with Multimodel Vision Transformers","date":"2024-11-25","arxiv_id":"2411.16989","n_code_links":0,"syntology":null},{"paper":"/paper/df-gnn-dynamic-fusion-framework-for-attention","slug":"df-gnn-dynamic-fusion-framework-for-attention","title":"DF-GNN: Dynamic Fusion Framework for Attention Graph Neural Networks on GPUs","date":"2024-11-25","arxiv_id":"2411.16127","n_code_links":1,"syntology":null},{"paper":null,"slug":"dynamic-self-distillation-via-previous-mini","title":"Dynamic Self-Distillation via Previous Mini-batches for Fine-tuning Small Language Models","date":"2024-11-25","arxiv_id":"2411.16991","n_code_links":0,"syntology":null},{"paper":null,"slug":"enhancing-answer-reliability-through-inter","title":"Enhancing Answer Reliability Through Inter-Model Consensus of Large Language Models","date":"2024-11-25","arxiv_id":"2411.16797","n_code_links":0,"syntology":null},{"paper":null,"slug":"enhancing-fluorescence-lifetime-parameter","title":"Enhancing Fluorescence Lifetime Parameter Estimation Accuracy with Differential Transformer Based Deep Learning Model Incorporating Pixelwise Instrument Response Function","date":"2024-11-25","arxiv_id":"2411.16896","n_code_links":0,"syntology":null},{"paper":null,"slug":"explainable-ai-approach-using-near-misses","title":"Explainable AI Approach using Near Misses Analysis","date":"2024-11-25","arxiv_id":"2411.16895","n_code_links":0,"syntology":null},{"paper":null,"slug":"factorized-visual-tokenization-and-generation","title":"Factorized Visual Tokenization and Generation","date":"2024-11-25","arxiv_id":"2411.16681","n_code_links":0,"syntology":null},{"paper":null,"slug":"fine-tuning-llms-with-noisy-data-for","title":"Fine-Tuning LLMs with Noisy Data for Political Argument Generation and Post Guidance","date":"2024-11-25","arxiv_id":"2411.16813","n_code_links":0,"syntology":null},{"paper":null,"slug":"human-calibrated-automated-testing-and","title":"Human-Calibrated Automated Testing and Validation of Generative Language Models","date":"2024-11-25","arxiv_id":"2411.16391","n_code_links":0,"syntology":null},{"paper":"/paper/interpreting-object-level-foundation-models","slug":"interpreting-object-level-foundation-models","title":"Interpreting Object-level Foundation Models via Visual Precision Search","date":"2024-11-25","arxiv_id":"2411.16198","n_code_links":2,"syntology":null},{"paper":"/paper/lab-rag-label-boosted-retrieval-augmented","slug":"lab-rag-label-boosted-retrieval-augmented","title":"LaB-RAG: Label Boosted Retrieval Augmented Generation for Radiology Report Generation","date":"2024-11-25","arxiv_id":"2411.16523","n_code_links":1,"syntology":null},{"paper":"/paper/marketgpt-developing-a-pre-trained","slug":"marketgpt-developing-a-pre-trained","title":"MarketGPT: Developing a Pre-trained transformer (GPT) for Modeling Financial Time Series","date":"2024-11-25","arxiv_id":"2411.16585","n_code_links":1,"syntology":{"ran":3,"of":3,"n_ran_checked":1,"n_instrument":2,"unverified":0,"pointer_only":3,"phrase":"3 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; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["aaron-wheeler/marketgpt"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"normxlogit-the-head-on-top-never-lies","title":"NormXLogit: The Head-on-Top Never Lies","date":"2024-11-25","arxiv_id":"2411.16252","n_code_links":0,"syntology":null},{"paper":null,"slug":"predictive-power-of-llms-in-financial-markets","title":"Predictive Power of LLMs in Financial Markets","date":"2024-11-25","arxiv_id":"2411.16569","n_code_links":0,"syntology":null},{"paper":"/paper/scaling-spike-driven-transformer-with","slug":"scaling-spike-driven-transformer-with","title":"Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training","date":"2024-11-25","arxiv_id":"2411.16061","n_code_links":1,"syntology":{"ran":2,"of":4,"n_ran_checked":2,"n_instrument":0,"unverified":2,"pointer_only":4,"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) · 2 unverified","official":{"repos":["biclab/spike-driven-transformer-v3"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/soft-transformers-for-continual-learning","slug":"soft-transformers-for-continual-learning","title":"Soft-TransFormers for Continual Learning","date":"2024-11-25","arxiv_id":"2411.16073","n_code_links":1,"syntology":null},{"paper":null,"slug":"solaris-a-foundation-model-of-the-sun","title":"Solaris: A Foundation Model of the Sun","date":"2024-11-25","arxiv_id":"2411.16339","n_code_links":0,"syntology":null},{"paper":null,"slug":"structformer-document-structure-based-masked","title":"StructFormer: Document Structure-based Masked Attention and its Impact on Language Model Pre-Training","date":"2024-11-25","arxiv_id":"2411.16618","n_code_links":0,"syntology":null},{"paper":null,"slug":"swin-fmri-transformer-predicts-early","title":"Swin fMRI Transformer Predicts Early Neurodevelopmental Outcomes from Neonatal fMRI","date":"2024-11-25","arxiv_id":"2412.07783","n_code_links":0,"syntology":null},{"paper":null,"slug":"syndiff-ad-improving-semantic-segmentation","title":"SynDiff-AD: Improving Semantic Segmentation and End-to-End Autonomous Driving with Synthetic Data from Latent Diffusion Models","date":"2024-11-25","arxiv_id":"2411.16776","n_code_links":0,"syntology":null},{"paper":null,"slug":"synthesising-handwritten-music-with-gans-a","title":"Synthesising Handwritten Music with GANs: A Comprehensive Evaluation of CycleWGAN, ProGAN, and DCGAN","date":"2024-11-25","arxiv_id":"2411.16405","n_code_links":0,"syntology":null},{"paper":null,"slug":"tree-transformers-are-an-ineffective-model-of","title":"Tree Transformers are an Ineffective Model of Syntactic Constituency","date":"2024-11-25","arxiv_id":"2411.16993","n_code_links":0,"syntology":null},{"paper":"/paper/ultrasam-a-foundation-model-for-ultrasound","slug":"ultrasam-a-foundation-model-for-ultrasound","title":"UltraSam: A Foundation Model for Ultrasound using Large Open-Access Segmentation Datasets","date":"2024-11-25","arxiv_id":"2411.16222","n_code_links":1,"syntology":null},{"paper":"/paper/vicon-vision-in-context-operator-networks-for","slug":"vicon-vision-in-context-operator-networks-for","title":"VICON: Vision In-Context Operator Networks for Multi-Physics Fluid Dynamics Prediction","date":"2024-11-25","arxiv_id":"2411.16063","n_code_links":1,"syntology":null},{"paper":null,"slug":"vq-sgen-a-vector-quantized-stroke","title":"VQ-SGen: A Vector Quantized Stroke Representation for Creative Sketch Generation","date":"2024-11-25","arxiv_id":"2411.16446","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-method-for-building-large-language-models","title":"A Method for Building Large Language Models with Predefined KV Cache Capacity","date":"2024-11-24","arxiv_id":"2411.15785","n_code_links":0,"syntology":null},{"paper":"/paper/beyond-adaptive-gradient-fast-controlled","slug":"beyond-adaptive-gradient-fast-controlled","title":"Beyond adaptive gradient: Fast-Controlled Minibatch Algorithm for large-scale optimization","date":"2024-11-24","arxiv_id":"2411.15795","n_code_links":1,"syntology":null},{"paper":null,"slug":"broad-critic-deep-actor-reinforcement","title":"Broad Critic Deep Actor Reinforcement Learning for Continuous Control","date":"2024-11-24","arxiv_id":"2411.15806","n_code_links":0,"syntology":null},{"paper":"/paper/development-of-pre-trained-transformer-based","slug":"development-of-pre-trained-transformer-based","title":"Development of Pre-Trained Transformer-based Models for the Nepali Language","date":"2024-11-24","arxiv_id":"2411.15734","n_code_links":0,"syntology":null},{"paper":null,"slug":"editable-deepsc-reliable-cross-modal-semantic","title":"Editable-DeepSC: Reliable Cross-Modal Semantic Communications for Facial Editing","date":"2024-11-24","arxiv_id":"2411.15702","n_code_links":0,"syntology":null},{"paper":null,"slug":"fixing-the-perspective-a-critical-examination","title":"Fixing the Perspective: A Critical Examination of Zero-1-to-3","date":"2024-11-24","arxiv_id":"2411.15706","n_code_links":0,"syntology":null},{"paper":null,"slug":"investigating-factuality-in-long-form-text","title":"Investigating Factuality in Long-Form Text Generation: The Roles of Self-Known and Self-Unknown","date":"2024-11-24","arxiv_id":"2411.15993","n_code_links":0,"syntology":null},{"paper":"/paper/libragrad-balancing-gradient-flow-for","slug":"libragrad-balancing-gradient-flow-for","title":"LibraGrad: Balancing Gradient Flow for Universally Better Vision Transformer Attributions","date":"2024-11-24","arxiv_id":"2411.16760","n_code_links":1,"syntology":null},{"paper":null,"slug":"ltcf-net-a-transformer-enhanced-dual-channel","title":"LTCF-Net: A Transformer-Enhanced Dual-Channel Fourier Framework for Low-Light Image Restoration","date":"2024-11-24","arxiv_id":"2411.15740","n_code_links":0,"syntology":null},{"paper":"/paper/medical-slice-transformer-improved-diagnosis","slug":"medical-slice-transformer-improved-diagnosis","title":"Medical Slice Transformer: Improved Diagnosis and Explainability on 3D Medical Images with DINOv2","date":"2024-11-24","arxiv_id":"2411.15802","n_code_links":1,"syntology":null},{"paper":"/paper/nimbus-secure-and-efficient-two-party","slug":"nimbus-secure-and-efficient-two-party","title":"Nimbus: Secure and Efficient Two-Party Inference for Transformers","date":"2024-11-24","arxiv_id":"2411.15707","n_code_links":1,"syntology":{"ran":0,"of":5,"n_ran_checked":0,"n_instrument":0,"unverified":5,"pointer_only":0,"phrase":"0 ran · 5 unverified","official":{"repos":["secretflow/spu"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":5,"ran_from_kinds":[]}}},{"paper":null,"slug":"ramie-retrieval-augmented-multi-task","title":"RAMIE: Retrieval-Augmented Multi-task Information Extraction with Large Language Models on Dietary Supplements","date":"2024-11-24","arxiv_id":"2411.15700","n_code_links":0,"syntology":null},{"paper":null,"slug":"transfair-transferring-fairness-from-ocular","title":"TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction","date":"2024-11-24","arxiv_id":"2412.00051","n_code_links":0,"syntology":null},{"paper":"/paper/a-comparative-analysis-of-transformer-and","slug":"a-comparative-analysis-of-transformer-and","title":"A Comparative Analysis of Transformer and LSTM Models for Detecting Suicidal Ideation on Reddit","date":"2024-11-23","arxiv_id":"2411.15404","n_code_links":1,"syntology":null}],"record_sha256":"f0cbc22cc2da7167e653d940429e25442d18b2da430db0a48e99d029b570e0f8","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}