{"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/speed/papers/5","list_of":"/method/speed","method":"SPEED","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":5,"pages_in_order":96,"rows_per_page":100,"rows":[401,500],"of":9573,"counts":{"archive_papers_tagged":9576,"with_a_code_link":3061,"where_syntology_ran_a_sample":779,"not_listed_spam_title":3,"listed":9573,"listed_where_code_ran":779,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":677,"every_run_a_failure_of_syntologys_instrument":102,"listed_with_a_run_with_no_instrument_failure":677,"listed_every_run_a_failure_of_syntologys_instrument":102,"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/speed","prev":"/method/speed/papers/4","next":"/method/speed/papers/6","papers":[{"paper":null,"slug":"a-robust-real-time-lane-detection-method-with","title":"A Robust Real-Time Lane Detection Method with Fog-Enhanced Feature Fusion for Foggy Conditions","date":"2025-04-08","arxiv_id":"2504.06121","n_code_links":0,"syntology":null},{"paper":"/paper/ddt-decoupled-diffusion-transformer-1","slug":"ddt-decoupled-diffusion-transformer-1","title":"DDT: Decoupled Diffusion Transformer","date":"2025-04-08","arxiv_id":"2504.05741","n_code_links":1,"syntology":null},{"paper":null,"slug":"meta-continual-learning-of-neural-fields","title":"Meta-Continual Learning of Neural Fields","date":"2025-04-08","arxiv_id":"2504.05806","n_code_links":0,"syntology":null},{"paper":null,"slug":"signal-and-backward-raman-pump-power","title":"Signal and Backward Raman Pump Power Optimization in Multi-Band Systems Using Fast Power Profile Estimation","date":"2025-04-08","arxiv_id":"2504.05726","n_code_links":0,"syntology":null},{"paper":null,"slug":"smart-exploration-in-reinforcement-learning","title":"Smart Exploration in Reinforcement Learning using Bounded Uncertainty Models","date":"2025-04-08","arxiv_id":"2504.05978","n_code_links":0,"syntology":null},{"paper":"/paper/why-is-normalization-necessary-for-linear","slug":"why-is-normalization-necessary-for-linear","title":"Why is Normalization Necessary for Linear Recommenders?","date":"2025-04-08","arxiv_id":"2504.05805","n_code_links":1,"syntology":null},{"paper":null,"slug":"cross-frame-otfs-parameter-estimation-based","title":"Cross-Frame OTFS Parameter Estimation Based On Chinese Remainder Theorem","date":"2025-04-07","arxiv_id":"2504.04811","n_code_links":0,"syntology":null},{"paper":null,"slug":"dion-a-communication-efficient-optimizer-for","title":"Dion: Distributed Orthonormalized Updates","date":"2025-04-07","arxiv_id":"2504.05295","n_code_links":0,"syntology":null},{"paper":"/paper/dynamic-vision-mamba","slug":"dynamic-vision-mamba","title":"Dynamic Vision Mamba","date":"2025-04-07","arxiv_id":"2504.04787","n_code_links":1,"syntology":null},{"paper":null,"slug":"dyttp-trajectory-prediction-with","title":"DyTTP: Trajectory Prediction with Normalization-Free Transformers","date":"2025-04-07","arxiv_id":"2504.05356","n_code_links":0,"syntology":null},{"paper":null,"slug":"hybrid-control-barrier-functions-for","title":"Hybrid Control Barrier Functions for Nonholonomic Multi-Agent Systems","date":"2025-04-07","arxiv_id":"2504.04937","n_code_links":0,"syntology":null},{"paper":null,"slug":"two-is-better-than-one-efficient-ensemble","title":"Two is Better than One: Efficient Ensemble Defense for Robust and Compact Models","date":"2025-04-07","arxiv_id":"2504.04747","n_code_links":0,"syntology":null},{"paper":null,"slug":"attention-driven-lplc2-neural-ensemble-model","title":"Attention-Driven LPLC2 Neural Ensemble Model for Multi-Target Looming Detection and Localization","date":"2025-04-06","arxiv_id":"2504.04477","n_code_links":0,"syntology":null},{"paper":null,"slug":"compression-laws-for-large-language-models","title":"Compression Laws for Large Language Models","date":"2025-04-06","arxiv_id":"2504.04342","n_code_links":0,"syntology":null},{"paper":null,"slug":"corrected-with-the-latest-version-make-robust","title":"Corrected with the Latest Version: Make Robust Asynchronous Federated Learning Possible","date":"2025-04-05","arxiv_id":"2504.04081","n_code_links":0,"syntology":null},{"paper":"/paper/towards-an-efficient-and-effective-en-route","slug":"towards-an-efficient-and-effective-en-route","title":"Towards An Efficient and Effective En Route Travel Time Estimation Framework","date":"2025-04-05","arxiv_id":"2504.04086","n_code_links":1,"syntology":null},{"paper":"/paper/vocalnet-speech-llm-with-multi-token","slug":"vocalnet-speech-llm-with-multi-token","title":"VocalNet: Speech LLM with Multi-Token Prediction for Faster and High-Quality Generation","date":"2025-04-05","arxiv_id":"2504.04060","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":2,"n_instrument":0,"unverified":0,"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) · 0 unverified","official":{"repos":["sjtu-omniagent/vocalnet"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"a-modular-energy-aware-framework-for","title":"A Modular Energy Aware Framework for Multicopter Modeling in Control and Planning Applications","date":"2025-04-04","arxiv_id":"2504.03256","n_code_links":0,"syntology":null},{"paper":null,"slug":"enhanced-penalty-based-bidirectional","title":"Enhanced Penalty-based Bidirectional Reinforcement Learning Algorithms","date":"2025-04-04","arxiv_id":"2504.03163","n_code_links":0,"syntology":null},{"paper":"/paper/learning-based-conformal-tube-mpc-for-safe","slug":"learning-based-conformal-tube-mpc-for-safe","title":"Learning-Based Conformal Tube MPC for Safe Control in Interactive Multi-Agent Systems","date":"2025-04-04","arxiv_id":"2504.03293","n_code_links":1,"syntology":null},{"paper":null,"slug":"nemotron-h-a-family-of-accurate-and-efficient","title":"Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models","date":"2025-04-04","arxiv_id":"2504.03624","n_code_links":0,"syntology":null},{"paper":null,"slug":"offline-and-distributional-reinforcement-1","title":"Offline and Distributional Reinforcement Learning for Wireless Communications","date":"2025-04-04","arxiv_id":"2504.03804","n_code_links":0,"syntology":null},{"paper":null,"slug":"opening-the-black-box-symbolic-regression","title":"Opening the Black-Box: Symbolic Regression with Kolmogorov-Arnold Networks for Energy Applications","date":"2025-04-04","arxiv_id":"2504.03913","n_code_links":0,"syntology":null},{"paper":"/paper/gmr-conv-an-efficient-rotation-and-reflection","slug":"gmr-conv-an-efficient-rotation-and-reflection","title":"GMR-Conv: An Efficient Rotation and Reflection Equivariant Convolution Kernel Using Gaussian Mixture Rings","date":"2025-04-03","arxiv_id":"2504.02819","n_code_links":1,"syntology":null},{"paper":null,"slug":"omnitalker-real-time-text-driven-talking-head","title":"OmniTalker: Real-Time Text-Driven Talking Head Generation with In-Context Audio-Visual Style Replication","date":"2025-04-03","arxiv_id":"2504.02433","n_code_links":0,"syntology":null},{"paper":null,"slug":"sequential-binary-hypothesis-testing-with","title":"Sequential Binary Hypothesis Testing with Competing Agents under Information Asymmetry","date":"2025-04-03","arxiv_id":"2504.02743","n_code_links":0,"syntology":null},{"paper":"/paper/skyreels-a2-compose-anything-in-video","slug":"skyreels-a2-compose-anything-in-video","title":"SkyReels-A2: Compose Anything in Video Diffusion Transformers","date":"2025-04-03","arxiv_id":"2504.02436","n_code_links":1,"syntology":null},{"paper":null,"slug":"uav-assisted-5g-networks-mobility-aware-3d","title":"UAV-Assisted 5G Networks: Mobility-Aware 3D Trajectory Optimization and Resource Allocation for Dynamic Environments","date":"2025-04-03","arxiv_id":"2504.02613","n_code_links":0,"syntology":null},{"paper":"/paper/a-conic-transformation-approach-for-solving","slug":"a-conic-transformation-approach-for-solving","title":"A Conic Transformation Approach for Solving the Perspective-Three-Point Problem","date":"2025-04-02","arxiv_id":"2504.01620","n_code_links":1,"syntology":null},{"paper":null,"slug":"accelerating-iov-intrusion-detection","title":"Accelerating IoV Intrusion Detection: Benchmarking GPU-Accelerated vs CPU-Based ML Libraries","date":"2025-04-02","arxiv_id":"2504.01905","n_code_links":0,"syntology":null},{"paper":null,"slug":"architect-your-landscape-approach-ayla-for","title":"Architect Your Landscape Approach (AYLA) for Optimizations in Deep Learning","date":"2025-04-02","arxiv_id":"2504.01875","n_code_links":0,"syntology":null},{"paper":null,"slug":"better-bill-gpt-comparing-large-language","title":"Better Bill GPT: Comparing Large Language Models against Legal Invoice Reviewers","date":"2025-04-02","arxiv_id":"2504.02881","n_code_links":0,"syntology":null},{"paper":null,"slug":"cause-or-trigger-from-philosophy-to-causal","title":"Cause or Trigger? From Philosophy to Causal Modeling","date":"2025-04-02","arxiv_id":"2504.01398","n_code_links":0,"syntology":null},{"paper":null,"slug":"factors-influencing-farmers-motivation-to","title":"Factors Influencing Farmers' Motivation to Adopt Smart Farm Technology in South Korea","date":"2025-04-02","arxiv_id":"2504.01795","n_code_links":0,"syntology":null},{"paper":"/paper/luminance-gs-adapting-3d-gaussian-splatting","slug":"luminance-gs-adapting-3d-gaussian-splatting","title":"Luminance-GS: Adapting 3D Gaussian Splatting to Challenging Lighting Conditions with View-Adaptive Curve Adjustment","date":"2025-04-02","arxiv_id":"2504.01503","n_code_links":1,"syntology":null},{"paper":null,"slug":"mdp-multidimensional-vision-model-pruning","title":"MDP: Multidimensional Vision Model Pruning with Latency Constraint","date":"2025-04-02","arxiv_id":"2504.02168","n_code_links":0,"syntology":null},{"paper":null,"slug":"online-fault-detection-and-classification-of","title":"Online Fault Detection and Classification of Chemical Process Systems Leveraging Statistical Process Control and Riemannian Geometric Analysis","date":"2025-04-02","arxiv_id":"2504.01276","n_code_links":0,"syntology":null},{"paper":null,"slug":"uaknn-label-distribution-learning-via","title":"UAKNN: Label Distribution Learning via Uncertainty-Aware KNN","date":"2025-04-02","arxiv_id":"2504.01508","n_code_links":0,"syntology":null},{"paper":"/paper/camosam2-motion-appearance-induced-auto","slug":"camosam2-motion-appearance-induced-auto","title":"CamoSAM2: Motion-Appearance Induced Auto-Refining Prompts for Video Camouflaged Object Detection","date":"2025-04-01","arxiv_id":"2504.00375","n_code_links":0,"syntology":null},{"paper":null,"slug":"communication-efficient-l-0-penalized-least","title":"Communication-Efficient l_0 Penalized Least Square","date":"2025-04-01","arxiv_id":"2504.00722","n_code_links":0,"syntology":null},{"paper":"/paper/in-context-learning-for-zero-shot-speed","slug":"in-context-learning-for-zero-shot-speed","title":"In-Context Learning for Zero-Shot Speed Estimation of BLDC motors","date":"2025-04-01","arxiv_id":"2504.00673","n_code_links":1,"syntology":null},{"paper":null,"slug":"neural-pruning-for-3d-scene-reconstruction","title":"Neural Pruning for 3D Scene Reconstruction: Efficient NeRF Acceleration","date":"2025-04-01","arxiv_id":"2504.00950","n_code_links":0,"syntology":null},{"paper":null,"slug":"real-time-navigation-for-autonomous-aerial","title":"Real-Time Navigation for Autonomous Aerial Vehicles Using Video","date":"2025-04-01","arxiv_id":"2504.01996","n_code_links":0,"syntology":null},{"paper":null,"slug":"adapting-vision-foundation-models-for-real","title":"Adapting Vision Foundation Models for Real-time Ultrasound Image Segmentation","date":"2025-03-31","arxiv_id":"2503.24368","n_code_links":0,"syntology":null},{"paper":null,"slug":"diffscale-continuous-downscaling-and-bias","title":"DiffScale: Continuous Downscaling and Bias Correction of Subseasonal Wind Speed Forecasts using Diffusion Models","date":"2025-03-31","arxiv_id":"2503.23893","n_code_links":0,"syntology":null},{"paper":null,"slug":"machine-learning-assisted-high-speed","title":"Machine Learning-assisted High-speed Combinatorial Optimization with Ising Machines for Dynamically Changing Problems","date":"2025-03-31","arxiv_id":"2503.23966","n_code_links":0,"syntology":null},{"paper":null,"slug":"orchmllm-orchestrate-multimodal-data-with","title":"Orchestrate Multimodal Data with Batch Post-Balancing to Accelerate Multimodal Large Language Model Training","date":"2025-03-31","arxiv_id":"2503.23830","n_code_links":0,"syntology":null},{"paper":null,"slug":"proposed-2mw-wind-turbine-for-use-in-the","title":"Proposed 2MW Wind Turbine for Use in the Governorate of Dhofar at the Sultanate of Oman","date":"2025-03-31","arxiv_id":"2504.07126","n_code_links":0,"syntology":null},{"paper":null,"slug":"reliable-traffic-monitoring-using-low-cost","title":"Reliable Traffic Monitoring Using Low-Cost Doppler Radar Units","date":"2025-03-31","arxiv_id":"2503.23926","n_code_links":0,"syntology":null},{"paper":"/paper/scalable-geometric-learning-with-correlation","slug":"scalable-geometric-learning-with-correlation","title":"Scalable Geometric Learning with Correlation-Based Functional Brain Networks","date":"2025-03-31","arxiv_id":"2503.23653","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-hybrid-reinforcement-learning-framework-for","title":"A Hybrid Reinforcement Learning Framework for Hard Latency Constrained Resource Scheduling","date":"2025-03-30","arxiv_id":"2504.03721","n_code_links":0,"syntology":null},{"paper":"/paper/efficient-dynamic-attention-3d-convolution","slug":"efficient-dynamic-attention-3d-convolution","title":"Efficient Dynamic Attention 3D Convolution for Hyperspectral Image Classification","date":"2025-03-30","arxiv_id":"2503.23472","n_code_links":1,"syntology":null},{"paper":null,"slug":"hyper-rag-combating-llm-hallucinations-using","title":"Hyper-RAG: Combating LLM Hallucinations using Hypergraph-Driven Retrieval-Augmented Generation","date":"2025-03-30","arxiv_id":"2504.08758","n_code_links":0,"syntology":null},{"paper":"/paper/kerneldna-dynamic-kernel-sharing-via","slug":"kerneldna-dynamic-kernel-sharing-via","title":"KernelDNA: Dynamic Kernel Sharing via Decoupled Naive Adapters","date":"2025-03-30","arxiv_id":"2503.23379","n_code_links":1,"syntology":null},{"paper":null,"slug":"make-autoregressive-great-again-diffusion","title":"Make Autoregressive Great Again: Diffusion-Free Graph Generation with Next-Scale Prediction","date":"2025-03-30","arxiv_id":"2503.23612","n_code_links":0,"syntology":null},{"paper":"/paper/reinforcement-learning-based-token-pruning-in","slug":"reinforcement-learning-based-token-pruning-in","title":"Reinforcement Learning-based Token Pruning in Vision Transformers: A Markov Game Approach","date":"2025-03-30","arxiv_id":"2503.23459","n_code_links":1,"syntology":null},{"paper":null,"slug":"visual-acuity-consistent-foveated-rendering","title":"Visual Acuity Consistent Foveated Rendering towards Retinal Resolution","date":"2025-03-30","arxiv_id":"2503.23410","n_code_links":0,"syntology":null},{"paper":null,"slug":"energy-aware-lane-planning-for-connected","title":"Energy-Aware Lane Planning for Connected Electric Vehicles in Urban Traffic: Design and Vehicle-in-the-Loop Validation","date":"2025-03-29","arxiv_id":"2503.23228","n_code_links":0,"syntology":null},{"paper":"/paper/freesplat-generalizable-3d-gaussian-splatting-1","slug":"freesplat-generalizable-3d-gaussian-splatting-1","title":"FreeSplat++: Generalizable 3D Gaussian Splatting for Efficient Indoor Scene Reconstruction","date":"2025-03-29","arxiv_id":"2503.22986","n_code_links":1,"syntology":null},{"paper":null,"slug":"incorporating-gnss-information-with-lidar","title":"Incorporating GNSS Information with LIDAR-Inertial Odometry for Accurate Land-Vehicle Localization","date":"2025-03-29","arxiv_id":"2503.23199","n_code_links":0,"syntology":null},{"paper":null,"slug":"multi-agent-reinforcement-learning-for-graph","title":"Multi-Agent Reinforcement Learning for Graph Discovery in D2D-Enabled Federated Learning","date":"2025-03-29","arxiv_id":"2503.23218","n_code_links":0,"syntology":null},{"paper":null,"slug":"real-time-video-prediction-with-fast-video","title":"Real-time Video Prediction With Fast Video Interpolation Model and Prediction Training","date":"2025-03-29","arxiv_id":"2503.23185","n_code_links":0,"syntology":null},{"paper":"/paper/supereio-self-supervised-event-feature","slug":"supereio-self-supervised-event-feature","title":"SuperEIO: Self-Supervised Event Feature Learning for Event Inertial Odometry","date":"2025-03-29","arxiv_id":"2503.22963","n_code_links":1,"syntology":null},{"paper":null,"slug":"disentangled-4d-gaussian-splatting-towards","title":"Disentangled 4D Gaussian Splatting: Towards Faster and More Efficient Dynamic Scene Rendering","date":"2025-03-28","arxiv_id":"2503.22159","n_code_links":0,"syntology":null},{"paper":null,"slug":"estimating-city-wide-operating-mode","title":"Estimating City-wide operating mode Distribution of Light-Duty Vehicles: A Neural Network-based Approach","date":"2025-03-28","arxiv_id":"2503.22118","n_code_links":0,"syntology":null},{"paper":null,"slug":"finding-unknown-unknowns-using-cyber-physical","title":"Finding Unknown Unknowns using Cyber-Physical System Simulators (Extended Report)","date":"2025-03-28","arxiv_id":"2503.22646","n_code_links":0,"syntology":null},{"paper":"/paper/quamba2-a-robust-and-scalable-post-training","slug":"quamba2-a-robust-and-scalable-post-training","title":"Quamba2: A Robust and Scalable Post-training Quantization Framework for Selective State Space Models","date":"2025-03-28","arxiv_id":"2503.22879","n_code_links":1,"syntology":null},{"paper":null,"slug":"sensorless-field-oriented-control-of-csi-fed","title":"Sensorless Field Oriented Control of CSI-Fed PMSM Drives Used in Submersible Pumps","date":"2025-03-28","arxiv_id":"2503.22855","n_code_links":0,"syntology":null},{"paper":"/paper/progressive-rendering-distillation-adapting","slug":"progressive-rendering-distillation-adapting","title":"Progressive Rendering Distillation: Adapting Stable Diffusion for Instant Text-to-Mesh Generation without 3D Data","date":"2025-03-27","arxiv_id":"2503.21694","n_code_links":1,"syntology":null},{"paper":null,"slug":"selection-of-the-fittest-or-selection-of-the","title":"Selection of the fittest or selection of the luckiest: the emergence of Goodhart's law in evolution","date":"2025-03-27","arxiv_id":"2503.21849","n_code_links":0,"syntology":null},{"paper":"/paper/vadmamba-exploring-state-space-models-for","slug":"vadmamba-exploring-state-space-models-for","title":"VADMamba: Exploring State Space Models for Fast Video Anomaly Detection","date":"2025-03-27","arxiv_id":"2503.21169","n_code_links":1,"syntology":null},{"paper":null,"slug":"3d-convolutional-neural-networks-for-improved","title":"3D Convolutional Neural Networks for Improved Detection of Intracranial bleeding in CT Imaging","date":"2025-03-26","arxiv_id":"2503.20306","n_code_links":0,"syntology":null},{"paper":null,"slug":"clean-clear-feasibility-of-safe-llm-clinical","title":"Clean & Clear: Feasibility of Safe LLM Clinical Guidance","date":"2025-03-26","arxiv_id":"2503.20953","n_code_links":0,"syntology":null},{"paper":"/paper/faster-parameter-efficient-tuning-with-token","slug":"faster-parameter-efficient-tuning-with-token","title":"Faster Parameter-Efficient Tuning with Token Redundancy Reduction","date":"2025-03-26","arxiv_id":"2503.20282","n_code_links":1,"syntology":null},{"paper":null,"slug":"improving-user-behavior-prediction-leveraging","title":"Improving User Behavior Prediction: Leveraging Annotator Metadata in Supervised Machine Learning Models","date":"2025-03-26","arxiv_id":"2503.21000","n_code_links":0,"syntology":null},{"paper":null,"slug":"physgen3d-crafting-a-miniature-interactive","title":"PhysGen3D: Crafting a Miniature Interactive World from a Single Image","date":"2025-03-26","arxiv_id":"2503.20746","n_code_links":0,"syntology":null},{"paper":null,"slug":"self-res-self-reflection-in-large-vision","title":"Self-ReS: Self-Reflection in Large Vision-Language Models for Long Video Understanding","date":"2025-03-26","arxiv_id":"2503.20362","n_code_links":0,"syntology":null},{"paper":null,"slug":"the-crucial-role-of-problem-formulation-in","title":"The Crucial Role of Problem Formulation in Real-World Reinforcement Learning","date":"2025-03-26","arxiv_id":"2503.20442","n_code_links":0,"syntology":null},{"paper":null,"slug":"two-for-the-price-of-one-integrating-large","title":"Two for the Price of One: Integrating Large Language Models to Learn Biophysical Interactions","date":"2025-03-26","arxiv_id":"2503.21017","n_code_links":0,"syntology":null},{"paper":null,"slug":"data-efficient-rapid-prediction-of-urban","title":"Data-efficient rapid prediction of urban airflow and temperature fields for complex building geometries","date":"2025-03-25","arxiv_id":"2503.19708","n_code_links":0,"syntology":null},{"paper":null,"slug":"eventmamba-enhancing-spatio-temporal-locality","title":"EventMamba: Enhancing Spatio-Temporal Locality with State Space Models for Event-Based Video Reconstruction","date":"2025-03-25","arxiv_id":"2503.19721","n_code_links":0,"syntology":null},{"paper":"/paper/genius-a-generative-framework-for-universal","slug":"genius-a-generative-framework-for-universal","title":"GENIUS: A Generative Framework for Universal Multimodal Search","date":"2025-03-25","arxiv_id":"2503.19868","n_code_links":1,"syntology":null},{"paper":"/paper/hogs-unified-near-and-far-object","slug":"hogs-unified-near-and-far-object","title":"HoGS: Unified Near and Far Object Reconstruction via Homogeneous Gaussian Splatting","date":"2025-03-25","arxiv_id":"2503.19232","n_code_links":1,"syntology":null},{"paper":null,"slug":"st-vlm-kinematic-instruction-tuning-for","title":"ST-VLM: Kinematic Instruction Tuning for Spatio-Temporal Reasoning in Vision-Language Models","date":"2025-03-25","arxiv_id":"2503.19355","n_code_links":0,"syntology":null},{"paper":"/paper/distilling-stereo-networks-for-performant-and","slug":"distilling-stereo-networks-for-performant-and","title":"Distilling Stereo Networks for Performant and Efficient Leaner Networks","date":"2025-03-24","arxiv_id":"2503.18544","n_code_links":1,"syntology":null},{"paper":null,"slug":"teller-real-time-streaming-audio-driven","title":"Teller: Real-Time Streaming Audio-Driven Portrait Animation with Autoregressive Motion Generation","date":"2025-03-24","arxiv_id":"2503.18429","n_code_links":0,"syntology":null},{"paper":null,"slug":"d-2lora-data-driven-lora-initialization-for","title":"$D^2LoRA$: Data-Driven LoRA Initialization for Low Resource Tasks","date":"2025-03-23","arxiv_id":"2503.18089","n_code_links":0,"syntology":null},{"paper":null,"slug":"can-llms-automate-fact-checking-article","title":"Can LLMs Automate Fact-Checking Article Writing?","date":"2025-03-22","arxiv_id":"2503.17684","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-new-segment-routing-method-with-swap-node","title":"A New Segment Routing method with Swap Node Selection Strategy Based on Deep Reinforcement Learning for Software Defined Network","date":"2025-03-21","arxiv_id":"2503.16914","n_code_links":0,"syntology":null},{"paper":null,"slug":"efficient-knowledge-distillation-via","title":"Efficient Knowledge Distillation via Curriculum Extraction","date":"2025-03-21","arxiv_id":"2503.17494","n_code_links":0,"syntology":null},{"paper":null,"slug":"hypernvd-accelerating-neural-video","title":"HyperNVD: Accelerating Neural Video Decomposition via Hypernetworks","date":"2025-03-21","arxiv_id":"2503.17276","n_code_links":0,"syntology":null},{"paper":null,"slug":"protogs-efficient-and-high-quality-rendering","title":"ProtoGS: Efficient and High-Quality Rendering with 3D Gaussian Prototypes","date":"2025-03-21","arxiv_id":"2503.17486","n_code_links":0,"syntology":null},{"paper":null,"slug":"real-time-diffusion-policies-for-games","title":"Real-Time Diffusion Policies for Games: Enhancing Consistency Policies with Q-Ensembles","date":"2025-03-21","arxiv_id":"2503.16978","n_code_links":0,"syntology":null},{"paper":null,"slug":"unicon-unidirectional-information-flow-for","title":"UniCon: Unidirectional Information Flow for Effective Control of Large-Scale Diffusion Models","date":"2025-03-21","arxiv_id":"2503.17221","n_code_links":0,"syntology":null},{"paper":null,"slug":"v-seek-accelerating-llm-reasoning-on-open","title":"V-Seek: Accelerating LLM Reasoning on Open-hardware Server-class RISC-V Platforms","date":"2025-03-21","arxiv_id":"2503.17422","n_code_links":0,"syntology":null},{"paper":null,"slug":"1000-fps-4d-gaussian-splatting-for-dynamic","title":"1000+ FPS 4D Gaussian Splatting for Dynamic Scene Rendering","date":"2025-03-20","arxiv_id":"2503.16422","n_code_links":0,"syntology":null},{"paper":"/paper/design-and-implementation-of-an-fpga-based","slug":"design-and-implementation-of-an-fpga-based","title":"Design and Implementation of an FPGA-Based Hardware Accelerator for Transformer","date":"2025-03-20","arxiv_id":"2503.16731","n_code_links":1,"syntology":null},{"paper":null,"slug":"gaurast-enhancing-gpu-triangle-rasterizers-to","title":"GauRast: Enhancing GPU Triangle Rasterizers to Accelerate 3D Gaussian Splatting","date":"2025-03-20","arxiv_id":"2503.16681","n_code_links":0,"syntology":null},{"paper":null,"slug":"hiq-lip-the-first-quantum-classical","title":"HiQ-Lip: The First Quantum-Classical Hierarchical Method for Global Lipschitz Constant Estimation of ReLU Networks","date":"2025-03-20","arxiv_id":"2503.16342","n_code_links":0,"syntology":null},{"paper":null,"slug":"iflame-interleaving-full-and-linear-attention","title":"iFlame: Interleaving Full and Linear Attention for Efficient Mesh Generation","date":"2025-03-20","arxiv_id":"2503.16653","n_code_links":0,"syntology":null}],"record_sha256":"6e9eee06b2e54a2de9b5e03ae6a0b40eae34fbc64bc30b76e3c27839a0ac1314","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}