{"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/softmax/papers/38","list_of":"/method/softmax","method":"Softmax","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":38,"pages_in_order":375,"rows_per_page":100,"rows":[3701,3800],"of":37443,"counts":{"archive_papers_tagged":37443,"with_a_code_link":15869,"where_syntology_ran_a_sample":4578,"not_listed_spam_title":0,"listed":37443,"listed_where_code_ran":4578,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":3835,"every_run_a_failure_of_syntologys_instrument":743,"listed_with_a_run_with_no_instrument_failure":3835,"listed_every_run_a_failure_of_syntologys_instrument":743,"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/softmax","prev":"/method/softmax/papers/37","next":"/method/softmax/papers/39","papers":[{"paper":"/paper/x2i-seamless-integration-of-multimodal","slug":"x2i-seamless-integration-of-multimodal","title":"X2I: Seamless Integration of Multimodal Understanding into Diffusion Transformer via Attention Distillation","date":"2025-03-08","arxiv_id":"2503.06134","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":0,"n_instrument":2,"unverified":0,"pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["oppo-mente-lab/x2i"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"your-large-vision-language-model-only-needs-a","title":"Your Large Vision-Language Model Only Needs A Few Attention Heads For Visual Grounding","date":"2025-03-08","arxiv_id":"2503.06287","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-hybrid-model-data-driven-solution-to","title":"A Hybrid Model/Data-Driven Solution to Channel, Position and Orientation Tracking in mmWave Vehicular Systems","date":"2025-03-07","arxiv_id":"2503.05091","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-real-time-multimodal-transformer-neural","title":"A Real-time Multimodal Transformer Neural Network-powered Wildfire Forecasting System","date":"2025-03-07","arxiv_id":"2503.05971","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-survey-on-sparse-autoencoders-interpreting","title":"A Survey on Sparse Autoencoders: Interpreting the Internal Mechanisms of Large Language Models","date":"2025-03-07","arxiv_id":"2503.05613","n_code_links":0,"syntology":null},{"paper":null,"slug":"bark-a-fully-bayesian-tree-kernel-for-black","title":"BARK: A Fully Bayesian Tree Kernel for Black-box Optimization","date":"2025-03-07","arxiv_id":"2503.05574","n_code_links":0,"syntology":null},{"paper":"/paper/casp-compression-of-large-multimodal-models","slug":"casp-compression-of-large-multimodal-models","title":"CASP: Compression of Large Multimodal Models Based on Attention Sparsity","date":"2025-03-07","arxiv_id":"2503.05936","n_code_links":1,"syntology":null},{"paper":"/paper/colfigphotoattnnet-reliable-finger-photo","slug":"colfigphotoattnnet-reliable-finger-photo","title":"ColFigPhotoAttnNet: Reliable Finger Photo Presentation Attack Detection Leveraging Window-Attention on Color Spaces","date":"2025-03-07","arxiv_id":"2503.05247","n_code_links":1,"syntology":null},{"paper":"/paper/comogaussian-continuous-motion-aware-gaussian","slug":"comogaussian-continuous-motion-aware-gaussian","title":"CoMoGaussian: Continuous Motion-Aware Gaussian Splatting from Motion-Blurred Images","date":"2025-03-07","arxiv_id":"2503.05332","n_code_links":1,"syntology":null},{"paper":null,"slug":"deep-frequency-attention-networks-for-single","title":"Deep Frequency Attention Networks for Single Snapshot Sparse Array Interpolation","date":"2025-03-07","arxiv_id":"2503.05486","n_code_links":0,"syntology":null},{"paper":"/paper/energy-free-sensing-and-context-recognition","slug":"energy-free-sensing-and-context-recognition","title":"Energy-Free Sensing and Context Recognition Using Photovoltaic Cells","date":"2025-03-07","arxiv_id":"2503.05406","n_code_links":1,"syntology":null},{"paper":null,"slug":"evaluating-large-language-models-in-code","title":"Evaluating Large Language Models in Code Generation: INFINITE Methodology for Defining the Inference Index","date":"2025-03-07","arxiv_id":"2503.05852","n_code_links":0,"syntology":null},{"paper":null,"slug":"evaluating-local-and-cloud-based-large","title":"Simulating and Analysing Human Survey Responses with Large Language Models: A Case Study in Energy Stated Preference","date":"2025-03-07","arxiv_id":"2503.10652","n_code_links":0,"syntology":null},{"paper":null,"slug":"evaluating-open-source-large-language-models","title":"Evaluating open-source Large Language Models for automated fact-checking","date":"2025-03-07","arxiv_id":"2503.05565","n_code_links":0,"syntology":null},{"paper":null,"slug":"explaining-the-unexplainable-a-systematic","title":"Explaining the Unexplainable: A Systematic Review of Explainable AI in Finance","date":"2025-03-07","arxiv_id":"2503.05966","n_code_links":0,"syntology":null},{"paper":null,"slug":"exploring-fmcw-radars-and-feature-maps-for","title":"Exploring FMCW Radars and Feature Maps for Activity Recognition: A Benchmark Study","date":"2025-03-07","arxiv_id":"2503.05629","n_code_links":0,"syntology":null},{"paper":"/paper/fastmap-fast-queries-initialization-based","slug":"fastmap-fast-queries-initialization-based","title":"FastMap: Fast Queries Initialization Based Vectorized HD Map Reconstruction Framework","date":"2025-03-07","arxiv_id":"2503.05492","n_code_links":1,"syntology":null},{"paper":null,"slug":"fmchs-advancing-traditional-chinese-medicine","title":"FMCHS: Advancing Traditional Chinese Medicine Herb Recommendation with Fusion of Multiscale Correlations of Herbs and Symptoms","date":"2025-03-07","arxiv_id":"2503.05167","n_code_links":0,"syntology":null},{"paper":null,"slug":"fmt-a-multimodal-pneumonia-detection-model","title":"FMT:A Multimodal Pneumonia Detection Model Based on Stacking MOE Framework","date":"2025-03-07","arxiv_id":"2503.05626","n_code_links":0,"syntology":null},{"paper":null,"slug":"gaussiancad-robust-self-supervised-cad","title":"GaussianCAD: Robust Self-Supervised CAD Reconstruction from Three Orthographic Views Using 3D Gaussian Splatting","date":"2025-03-07","arxiv_id":"2503.05161","n_code_links":0,"syntology":null},{"paper":null,"slug":"language-modelling-techniques-for-analysing","title":"Language modelling techniques for analysing the impact of human genetic variation","date":"2025-03-07","arxiv_id":"2503.10655","n_code_links":0,"syntology":null},{"paper":null,"slug":"leveraging-approximate-caching-for-faster","title":"Leveraging Approximate Caching for Faster Retrieval-Augmented Generation","date":"2025-03-07","arxiv_id":"2503.05530","n_code_links":0,"syntology":null},{"paper":null,"slug":"leveraging-semantic-type-dependencies-for","title":"Leveraging Semantic Type Dependencies for Clinical Named Entity Recognition","date":"2025-03-07","arxiv_id":"2503.05373","n_code_links":0,"syntology":null},{"paper":null,"slug":"lightweight-hypercomplex-mri-reconstruction-a","title":"Lightweight Hypercomplex MRI Reconstruction: A Generalized Kronecker-Parameterized Approach","date":"2025-03-07","arxiv_id":"2503.05063","n_code_links":0,"syntology":null},{"paper":null,"slug":"look-before-you-leap-using-serialized-state","title":"Look Before You Leap: Using Serialized State Machine for Language Conditioned Robotic Manipulation","date":"2025-03-07","arxiv_id":"2503.05114","n_code_links":0,"syntology":null},{"paper":null,"slug":"magicinfinite-generating-infinite-talking","title":"MagicInfinite: Generating Infinite Talking Videos with Your Words and Voice","date":"2025-03-07","arxiv_id":"2503.05978","n_code_links":0,"syntology":null},{"paper":"/paper/mastermindeval-a-simple-but-scalable","slug":"mastermindeval-a-simple-but-scalable","title":"MastermindEval: A Simple But Scalable Reasoning Benchmark","date":"2025-03-07","arxiv_id":"2503.05891","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["flairNLP/mastermind"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/medcam-osteocls-medical-context-aware","slug":"medcam-osteocls-medical-context-aware","title":"MedCAM-OsteoCls: Medical Context Aware Multimodal Classification of Knee Osteoarthritis","date":"2025-03-07","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"mol-cadiff-causality-aware-autoregressive","title":"Mol-CADiff: Causality-Aware Autoregressive Diffusion for Molecule Generation","date":"2025-03-07","arxiv_id":"2503.05499","n_code_links":0,"syntology":null},{"paper":"/paper/mptsnet-integrating-multiscale-periodic-local","slug":"mptsnet-integrating-multiscale-periodic-local","title":"MPTSNet: Integrating Multiscale Periodic Local Patterns and Global Dependencies for Multivariate Time Series Classification","date":"2025-03-07","arxiv_id":"2503.05582","n_code_links":1,"syntology":null},{"paper":null,"slug":"personalized-federated-learning-via-learning","title":"Personalized Federated Learning via Learning Dynamic Graphs","date":"2025-03-07","arxiv_id":"2503.05474","n_code_links":0,"syntology":null},{"paper":"/paper/pi-gps-enhancing-geometry-problem-solving-by","slug":"pi-gps-enhancing-geometry-problem-solving-by","title":"Pi-GPS: Enhancing Geometry Problem Solving by Unleashing the Power of Diagrammatic Information","date":"2025-03-07","arxiv_id":"2503.05543","n_code_links":0,"syntology":{"ran":7,"of":7,"n_ran_checked":5,"n_instrument":2,"unverified":0,"pointer_only":7,"phrase":"7 ran (of which 1 constructed an object rather than computing a result; 5 with no instrument failure: 1 honoured, 3 violated, 1 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","official":null}},{"paper":null,"slug":"quantifying-the-robustness-of-retrieval","title":"Quantifying the Robustness of Retrieval-Augmented Language Models Against Spurious Features in Grounding Data","date":"2025-03-07","arxiv_id":"2503.05587","n_code_links":0,"syntology":null},{"paper":"/paper/r1-searcher-incentivizing-the-search","slug":"r1-searcher-incentivizing-the-search","title":"R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning","date":"2025-03-07","arxiv_id":"2503.05592","n_code_links":5,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":null}},{"paper":null,"slug":"s2s-arena-evaluating-speech2speech-protocols","title":"S2S-Arena, Evaluating Speech2Speech Protocols on Instruction Following with Paralinguistic Information","date":"2025-03-07","arxiv_id":"2503.05085","n_code_links":0,"syntology":null},{"paper":"/paper/slim-attention-cut-your-context-memory-in","slug":"slim-attention-cut-your-context-memory-in","title":"Slim attention: cut your context memory in half without loss of accuracy -- K-cache is all you need for MHA","date":"2025-03-07","arxiv_id":"2503.05840","n_code_links":1,"syntology":null},{"paper":null,"slug":"splatpose-geometry-aware-6-dof-pose","title":"SplatPose: Geometry-Aware 6-DoF Pose Estimation from Single RGB Image via 3D Gaussian Splatting","date":"2025-03-07","arxiv_id":"2503.05174","n_code_links":0,"syntology":null},{"paper":"/paper/task-oriented-uncertainty-collaborative","slug":"task-oriented-uncertainty-collaborative","title":"Task-oriented Uncertainty Collaborative Learning for Label-Efficient Brain Tumor Segmentation","date":"2025-03-07","arxiv_id":"2503.05682","n_code_links":1,"syntology":null},{"paper":null,"slug":"tractable-representations-for-convergent","title":"Tractable Representations for Convergent Approximation of Distributional HJB Equations","date":"2025-03-07","arxiv_id":"2503.05563","n_code_links":0,"syntology":null},{"paper":null,"slug":"zero-shot-medical-event-prediction-using-a","title":"Zero-shot Medical Event Prediction Using a Generative Pre-trained Transformer on Electronic Health Records","date":"2025-03-07","arxiv_id":"2503.05893","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-generalist-cross-domain-molecular-learning","title":"A Generalist Cross-Domain Molecular Learning Framework for Structure-Based Drug Discovery","date":"2025-03-06","arxiv_id":"2503.04362","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-unified-framework-with-novel-metrics-for","title":"A Unified Framework with Novel Metrics for Evaluating the Effectiveness of XAI Techniques in LLMs","date":"2025-03-06","arxiv_id":"2503.05050","n_code_links":0,"syntology":null},{"paper":null,"slug":"beyond-rag-task-aware-kv-cache-compression","title":"Beyond RAG: Task-Aware KV Cache Compression for Comprehensive Knowledge Reasoning","date":"2025-03-06","arxiv_id":"2503.04973","n_code_links":0,"syntology":null},{"paper":null,"slug":"bicliqueencoder-an-efficient-method-for-link","title":"BicliqueEncoder: An Efficient Method for Link Prediction in Bipartite Networks using Formal Concept Analysis and Transformer Encoder","date":"2025-03-06","arxiv_id":"2503.07645","n_code_links":0,"syntology":null},{"paper":null,"slug":"can-we-optimize-deep-rl-policy-weights-as","title":"Can We Optimize Deep RL Policy Weights as Trajectory Modeling?","date":"2025-03-06","arxiv_id":"2503.04074","n_code_links":0,"syntology":null},{"paper":null,"slug":"chart-hqa-a-benchmark-for-hypothetical","title":"Chart-HQA: A Benchmark for Hypothetical Question Answering in Charts","date":"2025-03-06","arxiv_id":"2503.04095","n_code_links":0,"syntology":null},{"paper":null,"slug":"collapse-of-dense-retrievers-short-early-and","title":"Collapse of Dense Retrievers: Short, Early, and Literal Biases Outranking Factual Evidence","date":"2025-03-06","arxiv_id":"2503.05037","n_code_links":0,"syntology":null},{"paper":null,"slug":"compositional-causal-reasoning-evaluation-in","title":"Compositional Causal Reasoning Evaluation in Language Models","date":"2025-03-06","arxiv_id":"2503.04556","n_code_links":0,"syntology":null},{"paper":null,"slug":"conformal-forecasting-for-surgical-instrument","title":"Conformal forecasting for surgical instrument trajectory","date":"2025-03-06","arxiv_id":"2503.04191","n_code_links":0,"syntology":null},{"paper":null,"slug":"db-explore-automated-database-exploration-and","title":"DB-Explore: Automated Database Exploration and Instruction Synthesis for Text-to-SQL","date":"2025-03-06","arxiv_id":"2503.04959","n_code_links":0,"syntology":null},{"paper":null,"slug":"early-detection-of-mental-health-issues-using","title":"Early Detection of Mental Health Issues Using Social Media Posts","date":"2025-03-06","arxiv_id":"2503.07653","n_code_links":0,"syntology":null},{"paper":"/paper/frequency-based-alignment-of-eeg-and-audio","slug":"frequency-based-alignment-of-eeg-and-audio","title":"Frequency-Based Alignment of EEG and Audio Signals Using Contrastive Learning and SincNet for Auditory Attention Detection","date":"2025-03-06","arxiv_id":"2503.04156","n_code_links":1,"syntology":null},{"paper":"/paper/gate-shift-pose-enhancing-action-recognition","slug":"gate-shift-pose-enhancing-action-recognition","title":"Gate-Shift-Pose: Enhancing Action Recognition in Sports with Skeleton Information","date":"2025-03-06","arxiv_id":"2503.04470","n_code_links":1,"syntology":null},{"paper":"/paper/gbt-sam-a-parameter-efficient-depth-aware","slug":"gbt-sam-a-parameter-efficient-depth-aware","title":"GBT-SAM: Adapting a Foundational Deep Learning Model for Generalizable Brain Tumor Segmentation via Efficient Integration of Multi-Parametric MRI Data","date":"2025-03-06","arxiv_id":"2503.04325","n_code_links":1,"syntology":null},{"paper":null,"slug":"hedging-with-sparse-reward-reinforcement","title":"Hedging with Sparse Reward Reinforcement Learning","date":"2025-03-06","arxiv_id":"2503.04218","n_code_links":0,"syntology":null},{"paper":null,"slug":"high-precision-transformer-based-visual","title":"High-Precision Transformer-Based Visual Servoing for Humanoid Robots in Aligning Tiny Objects","date":"2025-03-06","arxiv_id":"2503.04862","n_code_links":0,"syntology":null},{"paper":null,"slug":"hilgen-hierarchically-informed-data","title":"HILGEN: Hierarchically-Informed Data Generation for Biomedical NER Using Knowledgebases and Large Language Models","date":"2025-03-06","arxiv_id":"2503.04930","n_code_links":0,"syntology":null},{"paper":"/paper/hybridnorm-towards-stable-and-efficient","slug":"hybridnorm-towards-stable-and-efficient","title":"HybridNorm: Towards Stable and Efficient Transformer Training via Hybrid Normalization","date":"2025-03-06","arxiv_id":"2503.04598","n_code_links":1,"syntology":null},{"paper":null,"slug":"in-depth-analysis-of-graph-based-rag-in-a","title":"In-depth Analysis of Graph-based RAG in a Unified Framework","date":"2025-03-06","arxiv_id":"2503.04338","n_code_links":0,"syntology":null},{"paper":null,"slug":"incentivizing-multi-tenant-split-federated","title":"Incentivizing Multi-Tenant Split Federated Learning for Foundation Models at the Network Edge","date":"2025-03-06","arxiv_id":"2503.04971","n_code_links":0,"syntology":null},{"paper":null,"slug":"interpretable-transformation-and-analysis-of","title":"Interpretable Transformation and Analysis of Timelines through Learning via Surprisability","date":"2025-03-06","arxiv_id":"2503.04502","n_code_links":0,"syntology":null},{"paper":"/paper/joint-masked-reconstruction-and-contrastive","slug":"joint-masked-reconstruction-and-contrastive","title":"Joint Masked Reconstruction and Contrastive Learning for Mining Interactions Between Proteins","date":"2025-03-06","arxiv_id":"2503.04650","n_code_links":1,"syntology":null},{"paper":null,"slug":"layer-specific-scaling-of-positional","title":"Layer-Specific Scaling of Positional Encodings for Superior Long-Context Modeling","date":"2025-03-06","arxiv_id":"2503.04355","n_code_links":0,"syntology":null},{"paper":null,"slug":"learning-transformer-based-world-models-with","title":"Learning Transformer-based World Models with Contrastive Predictive Coding","date":"2025-03-06","arxiv_id":"2503.04416","n_code_links":0,"syntology":null},{"paper":null,"slug":"learning-wideband-user-scheduling-and-hybrid","title":"Learning Wideband User Scheduling and Hybrid Precoding with Graph Neural Networks","date":"2025-03-06","arxiv_id":"2503.04233","n_code_links":0,"syntology":null},{"paper":null,"slug":"ledit-your-length-extrapolatable-diffusion","title":"LEDiT: Your Length-Extrapolatable Diffusion Transformer without Positional Encoding","date":"2025-03-06","arxiv_id":"2503.04344","n_code_links":0,"syntology":null},{"paper":"/paper/leveraging-large-language-models-to-address","slug":"leveraging-large-language-models-to-address","title":"Leveraging Large Language Models to Address Data Scarcity in Machine Learning: Applications in Graphene Synthesis","date":"2025-03-06","arxiv_id":"2503.04870","n_code_links":1,"syntology":null},{"paper":null,"slug":"multi-modal-summarization-in-model-based","title":"Multi-modal Summarization in Model-Based Engineering: Automotive Software Development Case Study","date":"2025-03-06","arxiv_id":"2503.04506","n_code_links":0,"syntology":null},{"paper":null,"slug":"scale-invariant-adversarial-attack-against","title":"Scale-Invariant Adversarial Attack against Arbitrary-scale Super-resolution","date":"2025-03-06","arxiv_id":"2503.04385","n_code_links":0,"syntology":null},{"paper":"/paper/toward-lightweight-and-fast-decoders-for","slug":"toward-lightweight-and-fast-decoders-for","title":"Toward Lightweight and Fast Decoders for Diffusion Models in Image and Video Generation","date":"2025-03-06","arxiv_id":"2503.04871","n_code_links":1,"syntology":null},{"paper":null,"slug":"towards-autonomous-reinforcement-learning-for","title":"Towards Autonomous Reinforcement Learning for Real-World Robotic Manipulation with Large Language Models","date":"2025-03-06","arxiv_id":"2503.04280","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-multimodal-framework-for-topic-propagation","title":"A Multimodal Framework for Topic Propagation Classification in Social Networks","date":"2025-03-05","arxiv_id":"2503.03112","n_code_links":0,"syntology":null},{"paper":"/paper/addressing-overprescribing-challenges-fine","slug":"addressing-overprescribing-challenges-fine","title":"Addressing Overprescribing Challenges: Fine-Tuning Large Language Models for Medication Recommendation Tasks","date":"2025-03-05","arxiv_id":"2503.03687","n_code_links":1,"syntology":{"ran":1,"of":3,"n_ran_checked":1,"n_instrument":0,"unverified":2,"pointer_only":0,"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) · 2 unverified","official":{"repos":["zzhustc2016/lamo"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"afford-x-generalizable-and-slim-affordance","title":"Afford-X: Generalizable and Slim Affordance Reasoning for Task-oriented Manipulation","date":"2025-03-05","arxiv_id":"2503.03556","n_code_links":0,"syntology":null},{"paper":null,"slug":"ahcptq-accurate-and-hardware-compatible-post","title":"AHCPTQ: Accurate and Hardware-Compatible Post-Training Quantization for Segment Anything Model","date":"2025-03-05","arxiv_id":"2503.03088","n_code_links":0,"syntology":null},{"paper":"/paper/all-atom-diffusion-transformers-unified","slug":"all-atom-diffusion-transformers-unified","title":"All-atom Diffusion Transformers: Unified generative modelling of molecules and materials","date":"2025-03-05","arxiv_id":"2503.03965","n_code_links":1,"syntology":{"ran":6,"of":7,"n_ran_checked":5,"n_instrument":1,"unverified":1,"pointer_only":7,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","official":{"repos":["facebookresearch/all-atom-diffusion-transformer"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/an-aspect-extraction-framework-using","slug":"an-aspect-extraction-framework-using","title":"An Aspect Extraction Framework using Different Embedding Types, Learning Models, and Dependency Structure","date":"2025-03-05","arxiv_id":"2503.03512","n_code_links":1,"syntology":null},{"paper":"/paper/analogical-reasoning-inside-large-language","slug":"analogical-reasoning-inside-large-language","title":"Analogical Reasoning Inside Large Language Models: Concept Vectors and the Limits of Abstraction","date":"2025-03-05","arxiv_id":"2503.03666","n_code_links":1,"syntology":null},{"paper":"/paper/banet-bilateral-aggregation-network-for","slug":"banet-bilateral-aggregation-network-for","title":"BANet: Bilateral Aggregation Network for Mobile Stereo Matching","date":"2025-03-05","arxiv_id":"2503.03259","n_code_links":1,"syntology":{"ran":8,"of":11,"n_ran_checked":6,"n_instrument":2,"unverified":3,"pointer_only":0,"phrase":"8 ran (of which 4 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 2 where Syntology's instrument failed) · 3 unverified","official":{"repos":["gangweix/banet"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":4,"n_ran_no_instrument_failure":6,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":"/paper/can-frontier-llms-replace-annotators-in","slug":"can-frontier-llms-replace-annotators-in","title":"Can Frontier LLMs Replace Annotators in Biomedical Text Mining? Analyzing Challenges and Exploring Solutions","date":"2025-03-05","arxiv_id":"2503.03261","n_code_links":1,"syntology":null},{"paper":null,"slug":"conformal-transformations-for-symmetric-power","title":"Conformal Transformations for Symmetric Power Transformers","date":"2025-03-05","arxiv_id":"2503.03269","n_code_links":0,"syntology":null},{"paper":null,"slug":"convergence-rates-for-softmax-gating-mixture","title":"Convergence Rates for Softmax Gating Mixture of Experts","date":"2025-03-05","arxiv_id":"2503.03213","n_code_links":0,"syntology":null},{"paper":null,"slug":"da-stgcn-4d-trajectory-prediction-based-on","title":"DA-STGCN: 4D Trajectory Prediction Based on Spatiotemporal Feature Extraction","date":"2025-03-05","arxiv_id":"2503.04823","n_code_links":0,"syntology":null},{"paper":null,"slug":"deictic-codes-demonstratives-and-reference-a","title":"Deictic Codes, Demonstratives, and Reference: A Step Toward Solving the Grounding Problem","date":"2025-03-05","arxiv_id":"2503.03495","n_code_links":0,"syntology":null},{"paper":null,"slug":"dtu-net-a-multi-scale-dilated-transformer","title":"DTU-Net: A Multi-Scale Dilated Transformer Network for Nonlinear Hyperspectral Unmixing","date":"2025-03-05","arxiv_id":"2503.03465","n_code_links":0,"syntology":null},{"paper":"/paper/dualdiff-dual-branch-diffusion-for-high","slug":"dualdiff-dual-branch-diffusion-for-high","title":"DualDiff+: Dual-Branch Diffusion for High-Fidelity Video Generation with Reward Guidance","date":"2025-03-05","arxiv_id":"2503.03689","n_code_links":1,"syntology":null},{"paper":"/paper/golden-cudgel-network-for-real-time-semantic","slug":"golden-cudgel-network-for-real-time-semantic","title":"Golden Cudgel Network for Real-Time Semantic Segmentation","date":"2025-03-05","arxiv_id":"2503.03325","n_code_links":1,"syntology":null},{"paper":null,"slug":"intermediate-task-transfer-learning","title":"Intermediate-Task Transfer Learning: Leveraging Sarcasm Detection for Stance Detection","date":"2025-03-05","arxiv_id":"2503.03172","n_code_links":0,"syntology":null},{"paper":null,"slug":"introduction-to-artificial-consciousness","title":"Introduction to Artificial Consciousness: History, Current Trends and Ethical Challenges","date":"2025-03-05","arxiv_id":"2503.05823","n_code_links":0,"syntology":null},{"paper":null,"slug":"knowledge-augmentation-in-federation","title":"Knowledge Augmentation in Federation: Rethinking What Collaborative Learning Can Bring Back to Decentralized Data","date":"2025-03-05","arxiv_id":"2503.03140","n_code_links":0,"syntology":null},{"paper":null,"slug":"l2r-learning-to-reduce-search-space-for","title":"Learning to Reduce Search Space for Generalizable Neural Routing Solver","date":"2025-03-05","arxiv_id":"2503.03137","n_code_links":0,"syntology":null},{"paper":null,"slug":"large-language-models-in-finance-estimating","title":"Large language models in finance : what is financial sentiment?","date":"2025-03-05","arxiv_id":"2503.03612","n_code_links":0,"syntology":null},{"paper":"/paper/ma-lot-multi-agent-lean-based-long-chain-of","slug":"ma-lot-multi-agent-lean-based-long-chain-of","title":"MA-LoT: Multi-Agent Lean-based Long Chain-of-Thought Reasoning enhances Formal Theorem Proving","date":"2025-03-05","arxiv_id":"2503.03205","n_code_links":1,"syntology":null},{"paper":null,"slug":"multi-view-depth-consistent-image-generation","title":"Multi-View Depth Consistent Image Generation Using Generative AI Models: Application on Architectural Design of University Buildings","date":"2025-03-05","arxiv_id":"2503.03068","n_code_links":0,"syntology":null},{"paper":null,"slug":"on-the-relation-between-speech-quality-and","title":"On the Relation Between Speech Quality and Quantized Latent Representations of Neural Codecs","date":"2025-03-05","arxiv_id":"2503.03304","n_code_links":0,"syntology":null},{"paper":null,"slug":"partial-convolution-meets-visual-attention","title":"Partial Convolution Meets Visual Attention","date":"2025-03-05","arxiv_id":"2503.03148","n_code_links":0,"syntology":null},{"paper":null,"slug":"pathrwkv-enabling-whole-slide-prediction-with","title":"PathRWKV: Enabling Whole Slide Prediction with Recurrent-Transformer","date":"2025-03-05","arxiv_id":"2503.03199","n_code_links":0,"syntology":null},{"paper":null,"slug":"personalized-federated-fine-tuning-for","title":"Personalized Federated Fine-tuning for Heterogeneous Data: An Automatic Rank Learning Approach via Two-Level LoRA","date":"2025-03-05","arxiv_id":"2503.03920","n_code_links":0,"syntology":null},{"paper":null,"slug":"petri-timo","title":"Petri Timo","date":"2025-03-05","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"powerattention-exponentially-scaling-of","title":"PowerAttention: Exponentially Scaling of Receptive Fields for Effective Sparse Attention","date":"2025-03-05","arxiv_id":"2503.03588","n_code_links":0,"syntology":null}],"record_sha256":"ca64374298fac57902a928a7f331e623b35aa11f4dcfb9248dd368ce9fd3fa0e","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}