{"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/position-wise-feed-forward-layer/papers/27","list_of":"/method/position-wise-feed-forward-layer","method":"Position-Wise Feed-Forward Layer","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":27,"pages_in_order":139,"rows_per_page":100,"rows":[2601,2700],"of":13895,"counts":{"archive_papers_tagged":13895,"with_a_code_link":6514,"where_syntology_ran_a_sample":2229,"not_listed_spam_title":0,"listed":13895,"listed_where_code_ran":2229,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":1902,"every_run_a_failure_of_syntologys_instrument":327,"listed_with_a_run_with_no_instrument_failure":1902,"listed_every_run_a_failure_of_syntologys_instrument":327,"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/position-wise-feed-forward-layer","prev":"/method/position-wise-feed-forward-layer/papers/26","next":"/method/position-wise-feed-forward-layer/papers/28","papers":[{"paper":null,"slug":"vmas-video-to-music-generation-via-semantic","title":"VMAS: Video-to-Music Generation via Semantic Alignment in Web Music Videos","date":"2024-09-11","arxiv_id":"2409.07450","n_code_links":0,"syntology":null},{"paper":null,"slug":"weather-informed-probabilistic-forecasting","title":"Weather-Informed Probabilistic Forecasting and Scenario Generation in Power Systems","date":"2024-09-11","arxiv_id":"2409.07637","n_code_links":0,"syntology":null},{"paper":null,"slug":"when-less-is-not-more-large-language-models","title":"Mapping Biomedical Ontology Terms to IDs: Effect of Domain Prevalence on Prediction Accuracy","date":"2024-09-11","arxiv_id":"2409.13746","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-dataset-for-evaluating-llm-based-evaluation","title":"A Dataset for Evaluating LLM-based Evaluation Functions for Research Question Extraction Task","date":"2024-09-10","arxiv_id":"2409.06883","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-practical-gated-recurrent-transformer","title":"A Practical Gated Recurrent Transformer Network Incorporating Multiple Fusions for Video Denoising","date":"2024-09-10","arxiv_id":"2409.06603","n_code_links":0,"syntology":null},{"paper":"/paper/adaptive-transformer-modelling-of-density","slug":"adaptive-transformer-modelling-of-density","title":"Adaptive Transformer Modelling of Density Function for Nonparametric Survival Analysis","date":"2024-09-10","arxiv_id":"2409.06209","n_code_links":1,"syntology":{"ran":8,"of":8,"n_ran_checked":6,"n_instrument":2,"unverified":0,"pointer_only":8,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 1 honoured, 0 violated, 5 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["xinz0419/unisurv"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"agileir-memory-efficient-group-shifted","title":"AgileIR: Memory-Efficient Group Shifted Windows Attention for Agile Image Restoration","date":"2024-09-10","arxiv_id":"2409.06206","n_code_links":0,"syntology":null},{"paper":null,"slug":"an-end-to-end-approach-for-chord-conditioned","title":"An End-to-End Approach for Chord-Conditioned Song Generation","date":"2024-09-10","arxiv_id":"2409.06307","n_code_links":0,"syntology":null},{"paper":"/paper/can-large-language-models-unlock-novel","slug":"can-large-language-models-unlock-novel","title":"Can Large Language Models Unlock Novel Scientific Research Ideas?","date":"2024-09-10","arxiv_id":"2409.06185","n_code_links":1,"syntology":{"ran":2,"of":11,"n_ran_checked":2,"n_instrument":0,"unverified":9,"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) · 9 unverified","official":{"repos":["sandeep82945/future-idea-generation"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":9,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"da-moe-towards-dynamic-expert-allocation-for","title":"DA-MoE: Towards Dynamic Expert Allocation for Mixture-of-Experts Models","date":"2024-09-10","arxiv_id":"2409.06669","n_code_links":0,"syntology":null},{"paper":"/paper/grouse-a-benchmark-to-evaluate-evaluators-in","slug":"grouse-a-benchmark-to-evaluate-evaluators-in","title":"GroUSE: A Benchmark to Evaluate Evaluators in Grounded Question Answering","date":"2024-09-10","arxiv_id":"2409.06595","n_code_links":1,"syntology":null},{"paper":null,"slug":"knowledge-distillation-via-query-selection","title":"Knowledge Distillation via Query Selection for Detection Transformer","date":"2024-09-10","arxiv_id":"2409.06443","n_code_links":0,"syntology":null},{"paper":null,"slug":"lightweight-multiscale-feature-fusion-super","title":"Lightweight single-image super-resolution network based on dual paths","date":"2024-09-10","arxiv_id":"2409.06590","n_code_links":0,"syntology":null},{"paper":"/paper/unilearn-enhancing-dynamic-facial-expression","slug":"unilearn-enhancing-dynamic-facial-expression","title":"Static for Dynamic: Towards a Deeper Understanding of Dynamic Facial Expressions Using Static Expression Data","date":"2024-09-10","arxiv_id":"2409.06154","n_code_links":1,"syntology":null},{"paper":"/paper/what-is-the-role-of-small-models-in-the-llm","slug":"what-is-the-role-of-small-models-in-the-llm","title":"What is the Role of Small Models in the LLM Era: A Survey","date":"2024-09-10","arxiv_id":"2409.06857","n_code_links":1,"syntology":null},{"paper":"/paper/2409-13727","slug":"2409-13727","title":"Classification performance and reproducibility of GPT-4 omni for information extraction from veterinary electronic health records","date":"2024-09-09","arxiv_id":"2409.13727","n_code_links":1,"syntology":null},{"paper":"/paper/2409-13728","slug":"2409-13728","title":"Rule Extrapolation in Language Models: A Study of Compositional Generalization on OOD Prompts","date":"2024-09-09","arxiv_id":"2409.13728","n_code_links":1,"syntology":null},{"paper":"/paper/abgpt-de-novo-antibody-design-via-generative","slug":"abgpt-de-novo-antibody-design-via-generative","title":"AbGPT: De Novo Antibody Design via Generative Language Modeling","date":"2024-09-09","arxiv_id":"2409.06090","n_code_links":1,"syntology":null},{"paper":null,"slug":"deep-generative-model-for-mechanical-system","title":"Deep Generative Model for Mechanical System Configuration Design","date":"2024-09-09","arxiv_id":"2409.06016","n_code_links":0,"syntology":null},{"paper":null,"slug":"drivescape-towards-high-resolution","title":"DriveScape: Towards High-Resolution Controllable Multi-View Driving Video Generation","date":"2024-09-09","arxiv_id":"2409.05463","n_code_links":0,"syntology":null},{"paper":null,"slug":"dsdformer-an-innovative-transformer-mamba","title":"DSDFormer: An Innovative Transformer-Mamba Framework for Robust High-Precision Driver Distraction Identification","date":"2024-09-09","arxiv_id":"2409.05587","n_code_links":0,"syntology":null},{"paper":null,"slug":"exploring-rich-subjective-quality-information","title":"Exploring Rich Subjective Quality Information for Image Quality Assessment in the Wild","date":"2024-09-09","arxiv_id":"2409.05540","n_code_links":0,"syntology":null},{"paper":null,"slug":"fairhome-a-fair-housing-and-fair-lending","title":"FairHome: A Fair Housing and Fair Lending Dataset","date":"2024-09-09","arxiv_id":"2409.05990","n_code_links":0,"syntology":null},{"paper":null,"slug":"identifying-the-sources-of-ideological-bias","title":"Identifying the sources of ideological bias in GPT models through linguistic variation in output","date":"2024-09-09","arxiv_id":"2409.06043","n_code_links":0,"syntology":null},{"paper":"/paper/retrofitting-temporal-graph-neural-networks","slug":"retrofitting-temporal-graph-neural-networks","title":"Retrofitting Temporal Graph Neural Networks with Transformer","date":"2024-09-09","arxiv_id":"2409.05477","n_code_links":1,"syntology":null},{"paper":"/paper/rotcatt-transunet-novel-deep-neural-network","slug":"rotcatt-transunet-novel-deep-neural-network","title":"RotCAtt-TransUNet++: Novel Deep Neural Network for Sophisticated Cardiac Segmentation","date":"2024-09-09","arxiv_id":"2409.05280","n_code_links":1,"syntology":null},{"paper":null,"slug":"towards-building-a-robust-knowledge-intensive","title":"Towards Building a Robust Knowledge Intensive Question Answering Model with Large Language Models","date":"2024-09-09","arxiv_id":"2409.05385","n_code_links":0,"syntology":null},{"paper":null,"slug":"zero-shot-outlier-detection-via-prior-data","title":"Zero-shot Outlier Detection via Prior-data Fitted Networks: Model Selection Bygone!","date":"2024-09-09","arxiv_id":"2409.05672","n_code_links":0,"syntology":null},{"paper":null,"slug":"audio-guided-fusion-techniques-for-multimodal","title":"Audio-Guided Fusion Techniques for Multimodal Emotion Analysis","date":"2024-09-08","arxiv_id":"2409.05007","n_code_links":0,"syntology":null},{"paper":null,"slug":"lung-detr-deformable-detection-transformer","title":"Lung-DETR: Deformable Detection Transformer for Sparse Lung Nodule Anomaly Detection","date":"2024-09-08","arxiv_id":"2409.05200","n_code_links":0,"syntology":null},{"paper":"/paper/activation-function-optimization-scheme-for","slug":"activation-function-optimization-scheme-for","title":"Activation Function Optimization Scheme for Image Classification","date":"2024-09-07","arxiv_id":"2409.04915","n_code_links":1,"syntology":null},{"paper":null,"slug":"adaptivefusion-adaptive-multi-modal-multi","title":"Towards Weather-Robust 3D Human Body Reconstruction: Millimeter-Wave Radar-Based Dataset, Benchmark, and Multi-Modal Fusion","date":"2024-09-07","arxiv_id":"2409.04851","n_code_links":0,"syntology":null},{"paper":"/paper/cross-attention-inspired-selective-state","slug":"cross-attention-inspired-selective-state","title":"Cross-attention Inspired Selective State Space Models for Target Sound Extraction","date":"2024-09-07","arxiv_id":"2409.04803","n_code_links":1,"syntology":{"ran":3,"of":4,"n_ran_checked":2,"n_instrument":1,"unverified":1,"pointer_only":4,"phrase":"3 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; 1 where Syntology's instrument failed) · 1 unverified","official":{"repos":["WuDH2000/CrossMamba"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"efficient-training-of-transformers-for","title":"Efficient Training of Transformers for Molecule Property Prediction on Small-scale Datasets","date":"2024-09-07","arxiv_id":"2409.04909","n_code_links":0,"syntology":null},{"paper":null,"slug":"muap-multi-step-adaptive-prompt-learning-for","title":"MuAP: Multi-step Adaptive Prompt Learning for Vision-Language Model with Missing Modality","date":"2024-09-07","arxiv_id":"2409.04693","n_code_links":0,"syntology":null},{"paper":null,"slug":"naptune-efficient-model-tuning-for-mood","title":"NapTune: Efficient Model Tuning for Mood Classification using Previous Night's Sleep Measures along with Wearable Time-series","date":"2024-09-07","arxiv_id":"2409.04723","n_code_links":0,"syntology":null},{"paper":null,"slug":"swin-transformer-for-robust-differentiation","title":"Swin Transformer for Robust Differentiation of Real and Synthetic Images: Intra- and Inter-Dataset Analysis","date":"2024-09-07","arxiv_id":"2409.04734","n_code_links":0,"syntology":null},{"paper":null,"slug":"vidlpro-a-underline-vid-eo-underline-l","title":"VidLPRO: A $\\underline{Vid}$eo-$\\underline{L}$anguage $\\underline{P}$re-training Framework for $\\underline{Ro}$botic and Laparoscopic Surgery","date":"2024-09-07","arxiv_id":"2409.04732","n_code_links":0,"syntology":null},{"paper":null,"slug":"actionflow-equivariant-accurate-and-efficient","title":"ActionFlow: Equivariant, Accurate, and Efficient Policies with Spatially Symmetric Flow Matching","date":"2024-09-06","arxiv_id":"2409.04576","n_code_links":0,"syntology":null},{"paper":null,"slug":"advancing-sem-based-nano-scale-defect","title":"Advancing SEM Based Nano-Scale Defect Analysis in Semiconductor Manufacturing for Advanced IC Nodes","date":"2024-09-06","arxiv_id":"2409.04310","n_code_links":0,"syntology":null},{"paper":"/paper/anymatch-efficient-zero-shot-entity-matching","slug":"anymatch-efficient-zero-shot-entity-matching","title":"AnyMatch -- Efficient Zero-Shot Entity Matching with a Small Language Model","date":"2024-09-06","arxiv_id":"2409.04073","n_code_links":1,"syntology":null},{"paper":null,"slug":"combining-llms-and-knowledge-graphs-to-reduce","title":"Combining LLMs and Knowledge Graphs to Reduce Hallucinations in Question Answering","date":"2024-09-06","arxiv_id":"2409.04181","n_code_links":0,"syntology":null},{"paper":null,"slug":"galla-graph-aligned-large-language-models-for","title":"GALLa: Graph Aligned Large Language Models for Improved Source Code Understanding","date":"2024-09-06","arxiv_id":"2409.04183","n_code_links":0,"syntology":null},{"paper":"/paper/qihoo-t2x-an-efficiency-focused-diffusion","slug":"qihoo-t2x-an-efficiency-focused-diffusion","title":"Qihoo-T2X: An Efficient Proxy-Tokenized Diffusion Transformer for Text-to-Any-Task","date":"2024-09-06","arxiv_id":"2409.04005","n_code_links":1,"syntology":null},{"paper":null,"slug":"retrieval-augmented-generation-based-incident","title":"Retrieval Augmented Generation-Based Incident Resolution Recommendation System for IT Support","date":"2024-09-06","arxiv_id":"2409.13707","n_code_links":0,"syntology":null},{"paper":null,"slug":"ui-jepa-towards-active-perception-of-user","title":"UI-JEPA: Towards Active Perception of User Intent through Onscreen User Activity","date":"2024-09-06","arxiv_id":"2409.04081","n_code_links":0,"syntology":null},{"paper":"/paper/cacer-clinical-concept-annotations-for-cancer","slug":"cacer-clinical-concept-annotations-for-cancer","title":"CACER: Clinical Concept Annotations for Cancer Events and Relations","date":"2024-09-05","arxiv_id":"2409.03905","n_code_links":1,"syntology":null},{"paper":"/paper/characterizing-massive-activations-of","slug":"characterizing-massive-activations-of","title":"Characterizing Massive Activations of Attention Mechanism in Graph Neural Networks","date":"2024-09-05","arxiv_id":"2409.03463","n_code_links":1,"syntology":null},{"paper":"/paper/lmlt-low-to-high-multi-level-vision","slug":"lmlt-low-to-high-multi-level-vision","title":"LMLT: Low-to-high Multi-Level Vision Transformer for Image Super-Resolution","date":"2024-09-05","arxiv_id":"2409.03516","n_code_links":1,"syntology":null},{"paper":null,"slug":"materialbench-evaluating-college-level","title":"MaterialBENCH: Evaluating College-Level Materials Science Problem-Solving Abilities of Large Language Models","date":"2024-09-05","arxiv_id":"2409.03161","n_code_links":0,"syntology":null},{"paper":"/paper/mvtn-a-multiscale-video-transformer-network","slug":"mvtn-a-multiscale-video-transformer-network","title":"MVTN: A Multiscale Video Transformer Network for Hand Gesture Recognition","date":"2024-09-05","arxiv_id":"2409.03890","n_code_links":1,"syntology":null},{"paper":"/paper/on-board-satellite-image-classification-for","slug":"on-board-satellite-image-classification-for","title":"Onboard Satellite Image Classification for Earth Observation: A Comparative Study of ViT Models","date":"2024-09-05","arxiv_id":"2409.03901","n_code_links":1,"syntology":null},{"paper":null,"slug":"why-mamba-is-effective-exploit-linear","title":"Why mamba is effective? Exploit Linear Transformer-Mamba Network for Multi-Modality Image Fusion","date":"2024-09-05","arxiv_id":"2409.03223","n_code_links":0,"syntology":null},{"paper":"/paper/xlam-a-family-of-large-action-models-to","slug":"xlam-a-family-of-large-action-models-to","title":"xLAM: A Family of Large Action Models to Empower AI Agent Systems","date":"2024-09-05","arxiv_id":"2409.03215","n_code_links":1,"syntology":null},{"paper":null,"slug":"causality-aware-transformer-networks-for","title":"Causality-Aware Transformer Networks for Robotic Navigation","date":"2024-09-04","arxiv_id":"2409.02669","n_code_links":0,"syntology":null},{"paper":null,"slug":"detecting-calls-to-action-in-multimodal","title":"Detecting Calls to Action in Multimodal Content: Analysis of the 2021 German Federal Election Campaign on Instagram","date":"2024-09-04","arxiv_id":"2409.02690","n_code_links":0,"syntology":null},{"paper":null,"slug":"historical-german-text-normalization-using","title":"Historical German Text Normalization Using Type- and Token-Based Language Modeling","date":"2024-09-04","arxiv_id":"2409.02841","n_code_links":0,"syntology":null},{"paper":"/paper/how-dreams-are-made-emulating-satellite","slug":"how-dreams-are-made-emulating-satellite","title":"How DREAMS are made: Emulating Satellite Galaxy and Subhalo Populations with Diffusion Models and Point Clouds","date":"2024-09-04","arxiv_id":"2409.02980","n_code_links":1,"syntology":{"ran":10,"of":11,"n_ran_checked":10,"n_instrument":0,"unverified":1,"pointer_only":0,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 0 violated, 10 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","official":{"repos":["trivnguyen/nehod_torch"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"how-privacy-savvy-are-large-language-models-a","title":"How Privacy-Savvy Are Large Language Models? A Case Study on Compliance and Privacy Technical Review","date":"2024-09-04","arxiv_id":"2409.02375","n_code_links":0,"syntology":null},{"paper":"/paper/hypothesizing-missing-causal-variables-with","slug":"hypothesizing-missing-causal-variables-with","title":"Hypothesizing Missing Causal Variables with LLMs","date":"2024-09-04","arxiv_id":"2409.02604","n_code_links":1,"syntology":null},{"paper":null,"slug":"iconformer-dynamic-parameter-efficient-tuning","title":"iConFormer: Dynamic Parameter-Efficient Tuning with Input-Conditioned Adaptation","date":"2024-09-04","arxiv_id":"2409.02838","n_code_links":0,"syntology":null},{"paper":null,"slug":"incorporating-like-minded-peers-to-overcome","title":"Incorporating Like-Minded Peers to Overcome Friend Data Sparsity in Session-Based Social Recommendations","date":"2024-09-04","arxiv_id":"2409.02702","n_code_links":0,"syntology":null},{"paper":null,"slug":"irrelevant-alternatives-bias-large-language","title":"Irrelevant Alternatives Bias Large Language Model Hiring Decisions","date":"2024-09-04","arxiv_id":"2409.15299","n_code_links":0,"syntology":null},{"paper":null,"slug":"leveraging-interpretability-in-the","title":"Leveraging Interpretability in the Transformer to Automate the Proactive Scaling of Cloud Resources","date":"2024-09-04","arxiv_id":"2409.03103","n_code_links":0,"syntology":null},{"paper":"/paper/longllava-scaling-multi-modal-llms-to-1000","slug":"longllava-scaling-multi-modal-llms-to-1000","title":"LongLLaVA: Scaling Multi-modal LLMs to 1000 Images Efficiently via a Hybrid Architecture","date":"2024-09-04","arxiv_id":"2409.02889","n_code_links":1,"syntology":{"ran":7,"of":7,"n_ran_checked":3,"n_instrument":4,"unverified":0,"pointer_only":7,"phrase":"7 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; 4 where Syntology's instrument failed) · 0 unverified","official":{"repos":["freedomintelligence/longllava"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/mobileunetr-a-lightweight-end-to-end-hybrid","slug":"mobileunetr-a-lightweight-end-to-end-hybrid","title":"MobileUNETR: A Lightweight End-To-End Hybrid Vision Transformer For Efficient Medical Image Segmentation","date":"2024-09-04","arxiv_id":"2409.03062","n_code_links":1,"syntology":null},{"paper":null,"slug":"mosmos-multi-organ-segmentation-facilitated","title":"MOSMOS: Multi-organ segmentation facilitated by medical report supervision","date":"2024-09-04","arxiv_id":"2409.02418","n_code_links":0,"syntology":null},{"paper":null,"slug":"robust-text-to-cypher-using-combination-of","title":"Robust Text-to-Cypher Using Combination of BERT, GraphSAGE, and Transformer (CoBGT) Model","date":"2024-09-04","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"towards-data-centric-face-anti-spoofing","title":"Towards Data-Centric Face Anti-Spoofing: Improving Cross-domain Generalization via Physics-based Data Synthesis","date":"2024-09-04","arxiv_id":"2409.03501","n_code_links":0,"syntology":null},{"paper":null,"slug":"training-universal-vocoders-with-feature","title":"Training Universal Vocoders with Feature Smoothing-Based Augmentation Methods for High-Quality TTS Systems","date":"2024-09-04","arxiv_id":"2409.02517","n_code_links":0,"syntology":null},{"paper":null,"slug":"waveletgpt-wavelets-meet-large-language","title":"Wavelet GPT: Wavelet Inspired Large Language Models","date":"2024-09-04","arxiv_id":"2409.12924","n_code_links":0,"syntology":null},{"paper":null,"slug":"1dcnntrans-bisindo-sign-language-interpreters","title":"1DCNNTrans: BISINDO Sign Language Interpreters in Improving the Inclusiveness of Public Services","date":"2024-09-03","arxiv_id":"2409.01975","n_code_links":0,"syntology":null},{"paper":null,"slug":"comparative-analysis-of-learning-based","title":"Comparative Analysis of Learning-Based Methods for Transient Stability Assessment","date":"2024-09-03","arxiv_id":"2409.02336","n_code_links":0,"syntology":null},{"paper":null,"slug":"f2former-when-fractional-fourier-meets-deep","title":"F2former: When Fractional Fourier Meets Deep Wiener Deconvolution and Selective Frequency Transformer for Image Deblurring","date":"2024-09-03","arxiv_id":"2409.02056","n_code_links":0,"syntology":null},{"paper":"/paper/frequency-spatial-entanglement-learning-for","slug":"frequency-spatial-entanglement-learning-for","title":"Frequency-Spatial Entanglement Learning for Camouflaged Object Detection","date":"2024-09-03","arxiv_id":"2409.01686","n_code_links":1,"syntology":{"ran":3,"of":6,"n_ran_checked":1,"n_instrument":2,"unverified":3,"pointer_only":2,"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) · 3 unverified","official":{"repos":["csysi/fsel"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"leveraging-large-language-models-for-solving","title":"Leveraging Large Language Models for Solving Rare MIP Challenges","date":"2024-09-03","arxiv_id":"2409.04464","n_code_links":0,"syntology":null},{"paper":null,"slug":"on-the-design-space-between-transformers-and","title":"On the Design Space Between Transformers and Recursive Neural Nets","date":"2024-09-03","arxiv_id":"2409.01531","n_code_links":0,"syntology":null},{"paper":null,"slug":"pmt-mae-dual-branch-self-supervised-learning","title":"PMT-MAE: Dual-Branch Self-Supervised Learning with Distillation for Efficient Point Cloud Classification","date":"2024-09-03","arxiv_id":"2409.02007","n_code_links":0,"syntology":null},{"paper":null,"slug":"self-instructed-derived-prompt-generation","title":"Self-Instructed Derived Prompt Generation Meets In-Context Learning: Unlocking New Potential of Black-Box LLMs","date":"2024-09-03","arxiv_id":"2409.01552","n_code_links":0,"syntology":null},{"paper":"/paper/spike-3d-human-pose-from-point-cloud","slug":"spike-3d-human-pose-from-point-cloud","title":"SPiKE: 3D Human Pose from Point Cloud Sequences","date":"2024-09-03","arxiv_id":"2409.01879","n_code_links":1,"syntology":null},{"paper":null,"slug":"the-ustc-nercslip-systems-for-the-chime-8","title":"The USTC-NERCSLIP Systems for the CHiME-8 NOTSOFAR-1 Challenge","date":"2024-09-03","arxiv_id":"2409.02041","n_code_links":0,"syntology":null},{"paper":null,"slug":"timedit-general-purpose-diffusion","title":"TimeDiT: General-purpose Diffusion Transformers for Time Series Foundation Model","date":"2024-09-03","arxiv_id":"2409.02322","n_code_links":0,"syntology":null},{"paper":"/paper/clibe-detecting-dynamic-backdoors-in","slug":"clibe-detecting-dynamic-backdoors-in","title":"CLIBE: Detecting Dynamic Backdoors in Transformer-based NLP Models","date":"2024-09-02","arxiv_id":"2409.01193","n_code_links":1,"syntology":{"ran":13,"of":19,"n_ran_checked":11,"n_instrument":2,"unverified":6,"pointer_only":3,"phrase":"13 ran (of which 0 constructed an object rather than computing a result; 11 with no instrument failure: 0 honoured, 0 violated, 11 with no contract checked; 2 where Syntology's instrument failed) · 6 unverified","official":{"repos":["raytsang123/clibe"],"state":"official (archive's flag): 13 ran","n_ran":13,"n_constructed":0,"n_ran_no_instrument_failure":11,"n_unverified":6,"ran_from_kinds":["official"]}}},{"paper":"/paper/esp-pct-enhanced-vr-semantic-performance","slug":"esp-pct-enhanced-vr-semantic-performance","title":"ESP-PCT: Enhanced VR Semantic Performance through Efficient Compression of Temporal and Spatial Redundancies in Point Cloud Transformers","date":"2024-09-02","arxiv_id":"2409.01216","n_code_links":1,"syntology":null},{"paper":null,"slug":"evidential-transformers-for-improved-image","title":"Evidential Transformers for Improved Image Retrieval","date":"2024-09-02","arxiv_id":"2409.01082","n_code_links":0,"syntology":null},{"paper":"/paper/large-language-models-versus-classical","slug":"large-language-models-versus-classical","title":"Large Language Models versus Classical Machine Learning: Performance in COVID-19 Mortality Prediction Using High-Dimensional Tabular Data","date":"2024-09-02","arxiv_id":"2409.02136","n_code_links":2,"syntology":null},{"paper":null,"slug":"multi-scale-temporal-fusion-transformer-for","title":"Multi-scale Temporal Fusion Transformer for Incomplete Vehicle Trajectory Prediction","date":"2024-09-02","arxiv_id":"2409.00904","n_code_links":0,"syntology":null},{"paper":"/paper/self-judge-selective-instruction-following","slug":"self-judge-selective-instruction-following","title":"Self-Judge: Selective Instruction Following with Alignment Self-Evaluation","date":"2024-09-02","arxiv_id":"2409.00935","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["nusnlp/Self-J"],"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":null,"slug":"the-role-of-transformer-models-in-advancing","title":"The Role of Transformer Models in Advancing Blockchain Technology: A Systematic Survey","date":"2024-09-02","arxiv_id":"2409.02139","n_code_links":0,"syntology":null},{"paper":null,"slug":"toolace-winning-the-points-of-llm-function","title":"ToolACE: Winning the Points of LLM Function Calling","date":"2024-09-02","arxiv_id":"2409.00920","n_code_links":0,"syntology":null},{"paper":"/paper/assessing-uhd-image-quality-from-aesthetics","slug":"assessing-uhd-image-quality-from-aesthetics","title":"Assessing UHD Image Quality from Aesthetics, Distortions, and Saliency","date":"2024-09-01","arxiv_id":"2409.00749","n_code_links":1,"syntology":null},{"paper":null,"slug":"attention-guided-multi-scale-interaction","title":"Attention-Guided Multi-scale Interaction Network for Face Super-Resolution","date":"2024-09-01","arxiv_id":"2409.00591","n_code_links":0,"syntology":null},{"paper":null,"slug":"deep-knowledge-infusion-for-explainable","title":"Deep Knowledge-Infusion For Explainable Depression Detection","date":"2024-09-01","arxiv_id":"2409.02122","n_code_links":0,"syntology":null},{"paper":"/paper/maskgct-zero-shot-text-to-speech-with-masked","slug":"maskgct-zero-shot-text-to-speech-with-masked","title":"MaskGCT: Zero-Shot Text-to-Speech with Masked Generative Codec Transformer","date":"2024-09-01","arxiv_id":"2409.00750","n_code_links":1,"syntology":null},{"paper":null,"slug":"proteinrpn-towards-accurate-protein-function","title":"ProteinRPN: Towards Accurate Protein Function Prediction with Graph-Based Region Proposals","date":"2024-09-01","arxiv_id":"2409.00610","n_code_links":0,"syntology":null},{"paper":"/paper/sample-efficient-diffusion-for-text-to-speech","slug":"sample-efficient-diffusion-for-text-to-speech","title":"Sample-Efficient Diffusion for Text-To-Speech Synthesis","date":"2024-09-01","arxiv_id":"2409.03717","n_code_links":1,"syntology":null},{"paper":"/paper/a-hybrid-transformer-mamba-network-for-single","slug":"a-hybrid-transformer-mamba-network-for-single","title":"A Hybrid Transformer-Mamba Network for Single Image Deraining","date":"2024-08-31","arxiv_id":"2409.00410","n_code_links":1,"syntology":null},{"paper":null,"slug":"an-empirical-study-on-information-extraction","title":"An Empirical Study on Information Extraction using Large Language Models","date":"2024-08-31","arxiv_id":"2409.00369","n_code_links":0,"syntology":null},{"paper":null,"slug":"chatting-up-attachment-using-llms-to-predict","title":"Chatting Up Attachment: Using LLMs to Predict Adult Bonds","date":"2024-08-31","arxiv_id":"2409.00347","n_code_links":0,"syntology":null},{"paper":null,"slug":"evaluating-the-performance-of-large-language-3","title":"Evaluating the Performance of Large Language Models in Competitive Programming: A Multi-Year, Multi-Grade Analysis","date":"2024-08-31","arxiv_id":"2409.09054","n_code_links":0,"syntology":null}],"record_sha256":"d1eef0801409e9dcbf57f7499b6fe2e2c857fdfaa061f941fcd4c3d109ae936c","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}