{"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/residual-connection/papers/25","list_of":"/method/residual-connection","method":"Residual Connection","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":25,"pages_in_order":285,"rows_per_page":100,"rows":[2401,2500],"of":28401,"counts":{"archive_papers_tagged":28401,"with_a_code_link":12847,"where_syntology_ran_a_sample":3897,"not_listed_spam_title":0,"listed":28401,"listed_where_code_ran":3897,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":3291,"every_run_a_failure_of_syntologys_instrument":606,"listed_with_a_run_with_no_instrument_failure":3291,"listed_every_run_a_failure_of_syntologys_instrument":606,"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/residual-connection","prev":"/method/residual-connection/papers/24","next":"/method/residual-connection/papers/26","papers":[{"paper":null,"slug":"bridging-dialects-translating-standard-bangla","title":"Bridging Dialects: Translating Standard Bangla to Regional Variants Using Neural Models","date":"2025-01-10","arxiv_id":"2501.05749","n_code_links":0,"syntology":null},{"paper":null,"slug":"cognospeak-an-automatic-remote-assessment-of","title":"CognoSpeak: an automatic, remote assessment of early cognitive decline in real-world conversational speech","date":"2025-01-10","arxiv_id":"2501.05755","n_code_links":0,"syntology":null},{"paper":null,"slug":"iconicity-in-large-language-models","title":"Iconicity in Large Language Models","date":"2025-01-10","arxiv_id":"2501.05643","n_code_links":0,"syntology":null},{"paper":"/paper/merging-feed-forward-sublayers-for-compressed","slug":"merging-feed-forward-sublayers-for-compressed","title":"Merging Feed-Forward Sublayers for Compressed Transformers","date":"2025-01-10","arxiv_id":"2501.06126","n_code_links":1,"syntology":null},{"paper":null,"slug":"mix-qvit-mixed-precision-vision-transformer","title":"Mix-QViT: Mixed-Precision Vision Transformer Quantization Driven by Layer Importance and Quantization Sensitivity","date":"2025-01-10","arxiv_id":"2501.06357","n_code_links":0,"syntology":null},{"paper":null,"slug":"model-inversion-in-split-learning-for","title":"Model Inversion in Split Learning for Personalized LLMs: New Insights from Information Bottleneck Theory","date":"2025-01-10","arxiv_id":"2501.05965","n_code_links":0,"syntology":null},{"paper":null,"slug":"mscvit-a-small-size-vit-architecture-with","title":"MSCViT: A Small-size ViT architecture with Multi-Scale Self-Attention Mechanism for Tiny Datasets","date":"2025-01-10","arxiv_id":"2501.06040","n_code_links":0,"syntology":null},{"paper":null,"slug":"multi-subject-open-set-personalization-in","title":"Multi-subject Open-set Personalization in Video Generation","date":"2025-01-10","arxiv_id":"2501.06187","n_code_links":0,"syntology":null},{"paper":"/paper/punctuation-s-semantic-role-between-brain-and","slug":"punctuation-s-semantic-role-between-brain-and","title":"Aligning Brain Activity with Advanced Transformer Models: Exploring the Role of Punctuation in Semantic Processing","date":"2025-01-10","arxiv_id":"2501.06278","n_code_links":1,"syntology":null},{"paper":null,"slug":"swin-x2s-reconstructing-3d-shape-from-2d","title":"Swin-X2S: Reconstructing 3D Shape from 2D Biplanar X-ray with Swin Transformers","date":"2025-01-10","arxiv_id":"2501.05961","n_code_links":0,"syntology":null},{"paper":"/paper/takunet-an-energy-efficient-cnn-for-real-time","slug":"takunet-an-energy-efficient-cnn-for-real-time","title":"TakuNet: an Energy-Efficient CNN for Real-Time Inference on Embedded UAV systems in Emergency Response Scenarios","date":"2025-01-10","arxiv_id":"2501.05880","n_code_links":1,"syntology":null},{"paper":null,"slug":"tts-transducer-end-to-end-speech-synthesis","title":"TTS-Transducer: End-to-End Speech Synthesis with Neural Transducer","date":"2025-01-10","arxiv_id":"2501.06320","n_code_links":0,"syntology":null},{"paper":"/paper/videorag-retrieval-augmented-generation-over","slug":"videorag-retrieval-augmented-generation-over","title":"VideoRAG: Retrieval-Augmented Generation over Video Corpus","date":"2025-01-10","arxiv_id":"2501.05874","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, 1 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["starsuzi/videorag"],"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":"weakly-supervised-segmentation-of-hyper","title":"Weakly Supervised Segmentation of Hyper-Reflective Foci with Compact Convolutional Transformers and SAM2","date":"2025-01-10","arxiv_id":"2501.05933","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-general-retrieval-augmented-generation","title":"A General Retrieval-Augmented Generation Framework for Multimodal Case-Based Reasoning Applications","date":"2025-01-09","arxiv_id":"2501.05030","n_code_links":0,"syntology":null},{"paper":null,"slug":"biomedical-relation-extraction-via-adaptive","title":"Biomedical Relation Extraction via Adaptive Document-Relation Cross-Mapping and Concept Unique Identifier","date":"2025-01-09","arxiv_id":"2501.05155","n_code_links":0,"syntology":null},{"paper":null,"slug":"dissim-finbert-text-simplification-for-core","title":"DisSim-FinBERT: Text Simplification for Core Message Extraction in Complex Financial Texts","date":"2025-01-09","arxiv_id":"2501.04959","n_code_links":0,"syntology":null},{"paper":"/paper/enhancing-plagiarism-detection-in-marathi","slug":"enhancing-plagiarism-detection-in-marathi","title":"Enhancing Plagiarism Detection in Marathi with a Weighted Ensemble of TF-IDF and BERT Embeddings for Low-Resource Language Processing","date":"2025-01-09","arxiv_id":"2501.05260","n_code_links":1,"syntology":null},{"paper":null,"slug":"explainable-ai-enhanced-deep-learning-for","title":"Explainable AI-Enhanced Deep Learning for Pumpkin Leaf Disease Detection: A Comparative Analysis of CNN Architectures","date":"2025-01-09","arxiv_id":"2501.05449","n_code_links":0,"syntology":null},{"paper":null,"slug":"large-language-models-streamline-automated","title":"Large language models streamline automated systematic review: A preliminary study","date":"2025-01-09","arxiv_id":"2502.15702","n_code_links":0,"syntology":null},{"paper":"/paper/llmquoter-enhancing-rag-capabilities-through","slug":"llmquoter-enhancing-rag-capabilities-through","title":"LLMQuoter: Enhancing RAG Capabilities Through Efficient Quote Extraction From Large Contexts","date":"2025-01-09","arxiv_id":"2501.05554","n_code_links":1,"syntology":null},{"paper":null,"slug":"longvitu-instruction-tuning-for-long-form","title":"LongViTU: Instruction Tuning for Long-Form Video Understanding","date":"2025-01-09","arxiv_id":"2501.05037","n_code_links":0,"syntology":null},{"paper":null,"slug":"openai-chatgpt-interprets-radiological-images","title":"OpenAI ChatGPT interprets Radiological Images: GPT-4 as a Medical Doctor for a Fast Check-Up","date":"2025-01-09","arxiv_id":"2501.06269","n_code_links":0,"syntology":null},{"paper":null,"slug":"optimizing-multitask-industrial-processes","title":"Optimizing Multitask Industrial Processes with Predictive Action Guidance","date":"2025-01-09","arxiv_id":"2501.05108","n_code_links":0,"syntology":null},{"paper":null,"slug":"rag-wm-an-efficient-black-box-watermarking","title":"RAG-WM: An Efficient Black-Box Watermarking Approach for Retrieval-Augmented Generation of Large Language Models","date":"2025-01-09","arxiv_id":"2501.05249","n_code_links":0,"syntology":null},{"paper":"/paper/spectf-transformers-enable-data-driven","slug":"spectf-transformers-enable-data-driven","title":"SpecTf: Transformers Enable Data-Driven Imaging Spectroscopy Cloud Detection","date":"2025-01-09","arxiv_id":"2501.04916","n_code_links":1,"syntology":null},{"paper":null,"slug":"the-dynamics-of-meaning-through-time","title":"The dynamics of meaning through time: Assessment of Large Language Models","date":"2025-01-09","arxiv_id":"2501.05552","n_code_links":0,"syntology":null},{"paper":null,"slug":"the-more-polypersonal-the-better-a-short-look","title":"The more polypersonal the better -- a short look on space geometry of fine-tuned layers","date":"2025-01-09","arxiv_id":"2501.05503","n_code_links":0,"syntology":null},{"paper":"/paper/uav-vla-vision-language-action-system-for","slug":"uav-vla-vision-language-action-system-for","title":"UAV-VLA: Vision-Language-Action System for Large Scale Aerial Mission Generation","date":"2025-01-09","arxiv_id":"2501.05014","n_code_links":1,"syntology":null},{"paper":null,"slug":"advancing-retrieval-augmented-generation-for","title":"Advancing Retrieval-Augmented Generation for Persian: Development of Language Models, Comprehensive Benchmarks, and Best Practices for Optimization","date":"2025-01-08","arxiv_id":"2501.04858","n_code_links":0,"syntology":null},{"paper":null,"slug":"circuit-complexity-bounds-for-visual","title":"Circuit Complexity Bounds for Visual Autoregressive Model","date":"2025-01-08","arxiv_id":"2501.04299","n_code_links":0,"syntology":null},{"paper":null,"slug":"comparison-of-neural-models-for-x-ray-image","title":"Comparison of Neural Models for X-ray Image Classification in COVID-19 Detection","date":"2025-01-08","arxiv_id":"2501.04196","n_code_links":0,"syntology":null},{"paper":null,"slug":"integrating-llms-with-its-recent-advances","title":"Integrating LLMs with ITS: Recent Advances, Potentials, Challenges, and Future Directions","date":"2025-01-08","arxiv_id":"2501.04437","n_code_links":0,"syntology":null},{"paper":null,"slug":"knowledge-retrieval-based-on-generative-ai","title":"Knowledge Retrieval Based on Generative AI","date":"2025-01-08","arxiv_id":"2501.04635","n_code_links":0,"syntology":null},{"paper":"/paper/mb-taylorformer-v2-improved-multi-branch","slug":"mb-taylorformer-v2-improved-multi-branch","title":"MB-TaylorFormer V2: Improved Multi-branch Linear Transformer Expanded by Taylor Formula for Image Restoration","date":"2025-01-08","arxiv_id":"2501.04486","n_code_links":2,"syntology":null},{"paper":null,"slug":"multi-task-retriever-fine-tuning-for-domain","title":"Multi-task retriever fine-tuning for domain-specific and efficient RAG","date":"2025-01-08","arxiv_id":"2501.04652","n_code_links":0,"syntology":null},{"paper":"/paper/quantum-inspired-embeddings-projection-and","slug":"quantum-inspired-embeddings-projection-and","title":"Quantum-inspired Embeddings Projection and Similarity Metrics for Representation Learning","date":"2025-01-08","arxiv_id":"2501.04591","n_code_links":1,"syntology":null},{"paper":null,"slug":"re-ranking-the-context-for-multimodal","title":"Re-ranking the Context for Multimodal Retrieval Augmented Generation","date":"2025-01-08","arxiv_id":"2501.04695","n_code_links":0,"syntology":null},{"paper":null,"slug":"scaling-large-language-model-training-on","title":"Scaling Large Language Model Training on Frontier with Low-Bandwidth Partitioning","date":"2025-01-08","arxiv_id":"2501.04266","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-value-mapping-virtual-staining-framework","title":"A Value Mapping Virtual Staining Framework for Large-scale Histological Imaging","date":"2025-01-07","arxiv_id":"2501.03592","n_code_links":0,"syntology":null},{"paper":null,"slug":"auxdepthnet-real-time-monocular-3d-object","title":"AuxDepthNet: Real-Time Monocular 3D Object Detection with Depth-Sensitive Features","date":"2025-01-07","arxiv_id":"2501.03700","n_code_links":0,"syntology":null},{"paper":null,"slug":"cfformer-cross-cnn-transformer-channel","title":"CFFormer: Cross CNN-Transformer Channel Attention and Spatial Feature Fusion for Improved Segmentation of Low Quality Medical Images","date":"2025-01-07","arxiv_id":"2501.03629","n_code_links":0,"syntology":null},{"paper":null,"slug":"efficient-and-accurate-tuberculosis-diagnosis","title":"Efficient and Accurate Tuberculosis Diagnosis: Attention Residual U-Net and Vision Transformer Based Detection Framework","date":"2025-01-07","arxiv_id":"2501.03538","n_code_links":0,"syntology":null},{"paper":"/paper/finding-a-voice-evaluating-african-american","slug":"finding-a-voice-evaluating-african-american","title":"Finding A Voice: Evaluating African American Dialect Generation for Chatbot Technology","date":"2025-01-07","arxiv_id":"2501.03441","n_code_links":1,"syntology":null},{"paper":"/paper/how-to-select-pre-trained-code-models-for","slug":"how-to-select-pre-trained-code-models-for","title":"How to Select Pre-Trained Code Models for Reuse? A Learning Perspective","date":"2025-01-07","arxiv_id":"2501.03783","n_code_links":1,"syntology":null},{"paper":"/paper/hp-bert-a-framework-for-longitudinal-study-of","slug":"hp-bert-a-framework-for-longitudinal-study-of","title":"HP-BERT: A framework for longitudinal study of Hinduphobia on social media via LLMs","date":"2025-01-07","arxiv_id":"2501.05482","n_code_links":1,"syntology":null},{"paper":null,"slug":"integrityai-at-genai-detection-task-2","title":"IntegrityAI at GenAI Detection Task 2: Detecting Machine-Generated Academic Essays in English and Arabic Using ELECTRA and Stylometry","date":"2025-01-07","arxiv_id":"2501.05476","n_code_links":0,"syntology":null},{"paper":null,"slug":"language-and-planning-in-robotic-navigation-a","title":"Language and Planning in Robotic Navigation: A Multilingual Evaluation of State-of-the-Art Models","date":"2025-01-07","arxiv_id":"2501.05478","n_code_links":0,"syntology":null},{"paper":"/paper/lm-net-a-light-weight-and-multi-scale-network","slug":"lm-net-a-light-weight-and-multi-scale-network","title":"LM-Net: A Light-weight and Multi-scale Network for Medical Image Segmentation","date":"2025-01-07","arxiv_id":"2501.03838","n_code_links":1,"syntology":null},{"paper":"/paper/mtrag-a-multi-turn-conversational-benchmark","slug":"mtrag-a-multi-turn-conversational-benchmark","title":"MTRAG: A Multi-Turn Conversational Benchmark for Evaluating Retrieval-Augmented Generation Systems","date":"2025-01-07","arxiv_id":"2501.03468","n_code_links":1,"syntology":null},{"paper":null,"slug":"practical-design-and-benchmarking-of","title":"Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding","date":"2025-01-07","arxiv_id":"2501.05479","n_code_links":0,"syntology":null},{"paper":null,"slug":"rag-check-evaluating-multimodal-retrieval","title":"RAG-Check: Evaluating Multimodal Retrieval Augmented Generation Performance","date":"2025-01-07","arxiv_id":"2501.03995","n_code_links":0,"syntology":null},{"paper":null,"slug":"reading-with-intent-neutralizing-intent","title":"Reading with Intent -- Neutralizing Intent","date":"2025-01-07","arxiv_id":"2501.03475","n_code_links":0,"syntology":null},{"paper":null,"slug":"snr-eq-jscc-joint-source-channel-coding-with","title":"SNR-EQ-JSCC: Joint Source-Channel Coding with SNR-Based Embedding and Query","date":"2025-01-07","arxiv_id":"2501.04732","n_code_links":0,"syntology":null},{"paper":"/paper/text-to-band-gap-pre-trained-language-models","slug":"text-to-band-gap-pre-trained-language-models","title":"Text to Band Gap: Pre-trained Language Models as Encoders for Semiconductor Band Gap Prediction","date":"2025-01-07","arxiv_id":"2501.03456","n_code_links":1,"syntology":null},{"paper":null,"slug":"three-dimensional-attention-transformer-for","title":"Three-dimensional attention Transformer for state evaluation in real-time strategy games","date":"2025-01-07","arxiv_id":"2501.03832","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-novel-vision-transformer-for-camera-lidar","title":"A Novel Vision Transformer for Camera-LiDAR Fusion based Traffic Object Segmentation","date":"2025-01-06","arxiv_id":"2501.02858","n_code_links":0,"syntology":null},{"paper":null,"slug":"adaptive-pruning-of-pretrained-transformer","title":"Adaptive Pruning of Pretrained Transformer via Differential Inclusions","date":"2025-01-06","arxiv_id":"2501.03289","n_code_links":0,"syntology":null},{"paper":null,"slug":"chat-beyond-contrastive-graph-transformer-for","title":"CHAT: Beyond Contrastive Graph Transformer for Link Prediction in Heterogeneous Networks","date":"2025-01-06","arxiv_id":"2501.02760","n_code_links":0,"syntology":null},{"paper":null,"slug":"developing-an-artificial-intelligence-tool","title":"Developing an Artificial Intelligence Tool for Personalized Breast Cancer Treatment Plans based on the NCCN Guidelines","date":"2025-01-06","arxiv_id":"2502.15698","n_code_links":0,"syntology":null},{"paper":null,"slug":"enhancing-robot-route-optimization-in-smart","title":"Intelligent logistics management robot path planning algorithm integrating transformer and GCN network","date":"2025-01-06","arxiv_id":"2501.02749","n_code_links":0,"syntology":null},{"paper":null,"slug":"flipedrag-black-box-opinion-manipulation","title":"FlippedRAG: Black-Box Opinion Manipulation Adversarial Attacks to Retrieval-Augmented Generation Models","date":"2025-01-06","arxiv_id":"2501.02968","n_code_links":0,"syntology":null},{"paper":"/paper/glog-csunet-enhancing-vision-transformers","slug":"glog-csunet-enhancing-vision-transformers","title":"GLoG-CSUnet: Enhancing Vision Transformers with Adaptable Radiomic Features for Medical Image Segmentation","date":"2025-01-06","arxiv_id":"2501.02788","n_code_links":1,"syntology":null},{"paper":null,"slug":"graph-based-retrieval-augmented-generation","title":"Graph-based Retrieval Augmented Generation for Dynamic Few-shot Text Classification","date":"2025-01-06","arxiv_id":"2501.02844","n_code_links":0,"syntology":null},{"paper":null,"slug":"integrating-language-image-prior-into-eeg","title":"Integrating Language-Image Prior into EEG Decoding for Cross-Task Zero-Calibration RSVP-BCI","date":"2025-01-06","arxiv_id":"2501.02841","n_code_links":0,"syntology":null},{"paper":"/paper/mixture-of-experts-graph-transformers-for","slug":"mixture-of-experts-graph-transformers-for","title":"Mixture-of-Experts Graph Transformers for Interpretable Particle Collision Detection","date":"2025-01-06","arxiv_id":"2501.03432","n_code_links":1,"syntology":null},{"paper":null,"slug":"multi-modal-one-shot-federated-ensemble","title":"Multi-Modal One-Shot Federated Ensemble Learning for Medical Data with Vision Large Language Model","date":"2025-01-06","arxiv_id":"2501.03292","n_code_links":0,"syntology":null},{"paper":null,"slug":"political-events-using-rag-with-llms","title":"Political Events using RAG with LLMs","date":"2025-01-06","arxiv_id":"2502.15701","n_code_links":0,"syntology":null},{"paper":null,"slug":"quim-rag-advancing-retrieval-augmented","title":"QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance","date":"2025-01-06","arxiv_id":"2501.02702","n_code_links":0,"syntology":null},{"paper":"/paper/salt-sales-autocompletion-linked-business","slug":"salt-sales-autocompletion-linked-business","title":"SALT: Sales Autocompletion Linked Business Tables Dataset","date":"2025-01-06","arxiv_id":"2501.03413","n_code_links":1,"syntology":null},{"paper":null,"slug":"sensorformer-cross-patch-attention-with","title":"Sensorformer: Cross-patch attention with global-patch compression is effective for high-dimensional multivariate time series forecasting","date":"2025-01-06","arxiv_id":"2501.03284","n_code_links":0,"syntology":null},{"paper":null,"slug":"sequence-complementor-complementing","title":"Sequence Complementor: Complementing Transformers For Time Series Forecasting with Learnable Sequences","date":"2025-01-06","arxiv_id":"2501.02735","n_code_links":0,"syntology":null},{"paper":null,"slug":"tree-based-rag-agent-recommendation-system-a","title":"Tree-based RAG-Agent Recommendation System: A Case Study in Medical Test Data","date":"2025-01-06","arxiv_id":"2501.02727","n_code_links":0,"syntology":null},{"paper":null,"slug":"vicsim-enhancing-victim-simulation-with","title":"VicSim: Enhancing Victim Simulation with Emotional and Linguistic Fidelity","date":"2025-01-06","arxiv_id":"2501.03139","n_code_links":0,"syntology":null},{"paper":"/paper/decoding-fmri-data-into-captions-using-prefix","slug":"decoding-fmri-data-into-captions-using-prefix","title":"Decoding fMRI Data into Captions using Prefix Language Modeling","date":"2025-01-05","arxiv_id":"2501.02570","n_code_links":1,"syntology":null},{"paper":null,"slug":"detrack-in-model-latent-denoising-learning","title":"DeTrack: In-model Latent Denoising Learning for Visual Object Tracking","date":"2025-01-05","arxiv_id":"2501.02467","n_code_links":0,"syntology":null},{"paper":null,"slug":"empowering-bengali-education-with-ai-solving","title":"Empowering Bengali Education with AI: Solving Bengali Math Word Problems through Transformer Models","date":"2025-01-05","arxiv_id":"2501.02599","n_code_links":0,"syntology":null},{"paper":null,"slug":"evaluating-large-language-models-against","title":"Evaluating Large Language Models Against Human Annotators in Latent Content Analysis: Sentiment, Political Leaning, Emotional Intensity, and Sarcasm","date":"2025-01-05","arxiv_id":"2501.02532","n_code_links":0,"syntology":null},{"paper":null,"slug":"gs-dit-advancing-video-generation-with-pseudo","title":"GS-DiT: Advancing Video Generation with Pseudo 4D Gaussian Fields through Efficient Dense 3D Point Tracking","date":"2025-01-05","arxiv_id":"2501.02690","n_code_links":0,"syntology":null},{"paper":null,"slug":"honkaichat-companions-from-anime-that-feel","title":"HonkaiChat: Companions from Anime that feel alive!","date":"2025-01-05","arxiv_id":"2501.03277","n_code_links":0,"syntology":null},{"paper":null,"slug":"lwfnet-coherent-doppler-wind-lidar-based","title":"LWFNet: Coherent Doppler Wind Lidar-Based Network for Wind Field Retrieval","date":"2025-01-05","arxiv_id":"2501.02613","n_code_links":0,"syntology":null},{"paper":null,"slug":"towards-new-benchmark-for-ai-alignment","title":"Towards New Benchmark for AI Alignment & Sentiment Analysis in Socially Important Issues: A Comparative Study of Human and LLMs in the Context of AGI","date":"2025-01-05","arxiv_id":"2501.02531","n_code_links":0,"syntology":null},{"paper":null,"slug":"context-aware-lemmatization-and-morphological","title":"Context Aware Lemmatization and Morphological Tagging Method in Turkish","date":"2025-01-04","arxiv_id":"2501.02361","n_code_links":0,"syntology":null},{"paper":null,"slug":"diabetic-retinopathy-detection-using-cnn-with","title":"Diabetic Retinopathy Detection Using CNN with Residual Block with DCGAN","date":"2025-01-04","arxiv_id":"2501.02300","n_code_links":0,"syntology":null},{"paper":null,"slug":"examining-the-robustness-of-homogeneity-bias","title":"Examining the Robustness of Homogeneity Bias to Hyperparameter Adjustments in GPT-4","date":"2025-01-04","arxiv_id":"2501.02211","n_code_links":0,"syntology":null},{"paper":null,"slug":"exploring-the-capabilities-and-limitations-of-1","title":"Exploring the Capabilities and Limitations of Large Language Models for Radiation Oncology Decision Support","date":"2025-01-04","arxiv_id":"2501.02346","n_code_links":0,"syntology":null},{"paper":"/paper/graph-aware-isomorphic-attention-for-adaptive","slug":"graph-aware-isomorphic-attention-for-adaptive","title":"Graph-Aware Isomorphic Attention for Adaptive Dynamics in Transformers","date":"2025-01-04","arxiv_id":"2501.02393","n_code_links":1,"syntology":null},{"paper":null,"slug":"knowledge-graph-retrieval-augmented","title":"Knowledge Graph Retrieval-Augmented Generation for LLM-based Recommendation","date":"2025-01-04","arxiv_id":"2501.02226","n_code_links":0,"syntology":null},{"paper":null,"slug":"llm-content-moderation-and-user-satisfaction","title":"LLM Content Moderation and User Satisfaction: Evidence from Response Refusals in Chatbot Arena","date":"2025-01-04","arxiv_id":"2501.03266","n_code_links":0,"syntology":null},{"paper":null,"slug":"plasma-cyclegan-plasma-biomarker-guided-mri","title":"Plasma-CycleGAN: Plasma Biomarker-Guided MRI to PET Cross-modality Translation Using Conditional CycleGAN","date":"2025-01-04","arxiv_id":"2501.02146","n_code_links":0,"syntology":null},{"paper":null,"slug":"the-application-of-large-language-models-in","title":"The Application of Large Language Models in Recommendation Systems","date":"2025-01-04","arxiv_id":"2501.02178","n_code_links":0,"syntology":null},{"paper":"/paper/a-separable-self-attention-inspired-by-the","slug":"a-separable-self-attention-inspired-by-the","title":"A Separable Self-attention Inspired by the State Space Model for Computer Vision","date":"2025-01-03","arxiv_id":"2501.02040","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-survey-on-large-language-models-with-some","title":"A Survey on Large Language Models with some Insights on their Capabilities and Limitations","date":"2025-01-03","arxiv_id":"2501.04040","n_code_links":0,"syntology":null},{"paper":null,"slug":"agentrefine-enhancing-agent-generalization","title":"AgentRefine: Enhancing Agent Generalization through Refinement Tuning","date":"2025-01-03","arxiv_id":"2501.01702","n_code_links":0,"syntology":null},{"paper":null,"slug":"bartpredict-empowering-iot-security-with-llm","title":"BARTPredict: Empowering IoT Security with LLM-Driven Cyber Threat Prediction","date":"2025-01-03","arxiv_id":"2501.01664","n_code_links":0,"syntology":null},{"paper":"/paper/bert4mimo-a-foundation-model-using-bert","slug":"bert4mimo-a-foundation-model-using-bert","title":"BERT4MIMO: A Foundation Model using BERT Architecture for Massive MIMO Channel State Information Prediction","date":"2025-01-03","arxiv_id":"2501.01802","n_code_links":1,"syntology":null},{"paper":null,"slug":"classifier-guided-captioning-across","title":"Classifier-Guided Captioning Across Modalities","date":"2025-01-03","arxiv_id":"2501.03183","n_code_links":0,"syntology":null},{"paper":"/paper/end-to-end-long-document-summarization-using","slug":"end-to-end-long-document-summarization-using","title":"End-to-End Long Document Summarization using Gradient Caching","date":"2025-01-03","arxiv_id":"2501.01805","n_code_links":0,"syntology":null},{"paper":null,"slug":"gobert-gene-ontology-graph-informed-bert-for","title":"GoBERT: Gene Ontology Graph Informed BERT for Universal Gene Function Prediction","date":"2025-01-03","arxiv_id":"2501.01930","n_code_links":0,"syntology":null},{"paper":null,"slug":"improving-transducer-based-spoken-language","title":"Improving Transducer-Based Spoken Language Understanding with Self-Conditioned CTC and Knowledge Transfer","date":"2025-01-03","arxiv_id":"2501.01936","n_code_links":0,"syntology":null}],"record_sha256":"64c0fefa17ba7112b4f108020f101875155f514633d531e83485cbe8d72bd0e2","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}