{"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":"/task/diversity/papers/37","list_of":"/task/diversity","task":"Diversity","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":37,"pages_in_order":91,"rows_per_page":100,"rows":[3601,3700],"of":9051,"counts":{"archive_papers_tagged":9051,"with_a_code_link":3166,"where_syntology_ran_a_sample":890,"not_listed_spam_title":0,"listed":9051,"listed_where_code_ran":890,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":736,"every_run_a_failure_of_syntologys_instrument":154,"listed_with_a_run_with_no_instrument_failure":736,"listed_every_run_a_failure_of_syntologys_instrument":154,"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":"/task/diversity","prev":"/task/diversity/papers/36","next":"/task/diversity/papers/38","papers":[{"url":null,"slug":"group-relative-policy-optimization-for-image","title":"Group Relative Policy Optimization for Image Captioning","date":"2025-03-03","arxiv_id":"2503.01333","repositories_listed":0,"syntology":null},{"url":null,"slug":"hi-series-algorithms-a-hybrid-of-substance","title":"HI-Series Algorithms A Hybrid of Substance Diffusion Algorithm and Collaborative Filtering","date":"2025-03-03","arxiv_id":"2503.01305","repositories_listed":0,"syntology":null},{"url":null,"slug":"hypergraph-foundation-model","title":"Hypergraph Foundation Model","date":"2025-03-03","arxiv_id":"2503.01203","repositories_listed":0,"syntology":null},{"url":null,"slug":"samplemix-a-sample-wise-pre-training-data","title":"SampleMix: A Sample-wise Pre-training Data Mixing Strategey by Coordinating Data Quality and Diversity","date":"2025-03-03","arxiv_id":"2503.01506","repositories_listed":0,"syntology":null},{"url":null,"slug":"2503-00691","title":"How Diversely Can Language Models Solve Problems? Exploring the Algorithmic Diversity of Model-Generated Code","date":"2025-03-02","arxiv_id":"2503.00691","repositories_listed":0,"syntology":null},{"url":null,"slug":"2503-00489","title":"Embracing Diversity: A Multi-Perspective Approach with Soft Labels","date":"2025-03-01","arxiv_id":"2503.00489","repositories_listed":0,"syntology":null},{"url":null,"slug":"jointly-understand-your-command-and-intention","title":"Jointly Understand Your Command and Intention:Reciprocal Co-Evolution between Scene-Aware 3D Human Motion Synthesis and Analysis","date":"2025-03-01","arxiv_id":"2503.00371","repositories_listed":0,"syntology":null},{"url":null,"slug":"autoencoder-based-framework-to-capture","title":"Autoencoder-Based Framework to Capture Vocabulary Quality in NLP","date":"2025-02-28","arxiv_id":"2503.00209","repositories_listed":0,"syntology":null},{"url":null,"slug":"innovation-exnovation-dynamics-on-trees-and","title":"Innovation-exnovation dynamics on trees and trusses","date":"2025-02-28","arxiv_id":"2502.21072","repositories_listed":0,"syntology":null},{"url":null,"slug":"modeling-cell-differentiation-in","title":"Modeling cell differentiation in neuroblastoma: insights into development, malignancy, and treatment relapse","date":"2025-02-28","arxiv_id":"2502.20939","repositories_listed":0,"syntology":null},{"url":null,"slug":"supporting-the-development-of-machine","title":"Supporting the development of Machine Learning for fundamental science in a federated Cloud with the AI_INFN platform","date":"2025-02-28","arxiv_id":"2502.21266","repositories_listed":0,"syntology":null},{"url":null,"slug":"adage-active-defenses-against-gnn-extraction","title":"ADAGE: Active Defenses Against GNN Extraction","date":"2025-02-27","arxiv_id":"2503.00065","repositories_listed":0,"syntology":null},{"url":null,"slug":"diffcss-diverse-and-expressive-conversational","title":"DiffCSS: Diverse and Expressive Conversational Speech Synthesis with Diffusion Models","date":"2025-02-27","arxiv_id":"2502.19924","repositories_listed":0,"syntology":null},{"url":null,"slug":"identifiable-multi-view-causal-discovery","title":"Identifiable Multi-View Causal Discovery Without Non-Gaussianity","date":"2025-02-27","arxiv_id":"2502.20115","repositories_listed":0,"syntology":null},{"url":null,"slug":"livs-a-pluralistic-alignment-dataset-for","title":"LIVS: A Pluralistic Alignment Dataset for Inclusive Public Spaces","date":"2025-02-27","arxiv_id":"2503.01894","repositories_listed":0,"syntology":null},{"url":null,"slug":"revisiting-self-consistency-from-dynamic","title":"Revisiting Self-Consistency from Dynamic Distributional Alignment Perspective on Answer Aggregation","date":"2025-02-27","arxiv_id":"2502.19830","repositories_listed":0,"syntology":null},{"url":null,"slug":"ruranet-an-unsupervised-learning-method-for","title":"RURANET++: An Unsupervised Learning Method for Diabetic Macular Edema Based on SCSE Attention Mechanisms and Dynamic Multi-Projection Head Clustering","date":"2025-02-27","arxiv_id":"2502.20224","repositories_listed":0,"syntology":null},{"url":null,"slug":"low-confidence-gold-refining-low-confidence","title":"Low-Confidence Gold: Refining Low-Confidence Samples for Efficient Instruction Tuning","date":"2025-02-26","arxiv_id":"2502.18978","repositories_listed":0,"syntology":null},{"url":null,"slug":"where-are-we-evaluating-llm-performance-on","title":"Where Are We? Evaluating LLM Performance on African Languages","date":"2025-02-26","arxiv_id":"2502.19582","repositories_listed":0,"syntology":null},{"url":null,"slug":"effect-of-gender-fair-job-description-on","title":"Effect of Gender Fair Job Description on Generative AI Images","date":"2025-02-25","arxiv_id":"2503.05769","repositories_listed":0,"syntology":null},{"url":null,"slug":"endive-a-cross-dialect-benchmark-for-fairness","title":"EnDive: A Cross-Dialect Benchmark for Fairness and Performance in Large Language Models","date":"2025-02-25","arxiv_id":"2504.07100","repositories_listed":0,"syntology":null},{"url":null,"slug":"mpo-an-efficient-post-processing-framework","title":"MPO: An Efficient Post-Processing Framework for Mixing Diverse Preference Alignment","date":"2025-02-25","arxiv_id":"2502.18699","repositories_listed":0,"syntology":null},{"url":null,"slug":"smt-lia-sampling-with-high-diversity","title":"SMT(LIA) Sampling with High Diversity","date":"2025-02-25","arxiv_id":"2503.04782","repositories_listed":0,"syntology":null},{"url":null,"slug":"airis2-a-smart-gateway-diversity-algorithm","title":"AIRIS2 : a Smart Gateway Diversity Algorithm for Very High-Throughput Satellite Systems","date":"2025-02-24","arxiv_id":"2502.17181","repositories_listed":0,"syntology":null},{"url":null,"slug":"clep-gan-an-innovative-approach-to-subject","title":"CLEP-GAN: An Innovative Approach to Subject-Independent ECG Reconstruction from PPG Signals","date":"2025-02-24","arxiv_id":"2502.17536","repositories_listed":0,"syntology":null},{"url":null,"slug":"entailment-preserving-first-order-logic","title":"Entailment-Preserving First-order Logic Representations in Natural Language Entailment","date":"2025-02-24","arxiv_id":"2502.16757","repositories_listed":0,"syntology":null},{"url":null,"slug":"hybridlinker-topology-guided-posterior","title":"HybridLinker: Topology-Guided Posterior Sampling for Enhanced Diversity and Validity in 3D Molecular Linker Generation","date":"2025-02-24","arxiv_id":"2502.17349","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-the-transferability-of-adversarial-9","title":"Improving the Transferability of Adversarial Examples by Inverse Knowledge Distillation","date":"2025-02-24","arxiv_id":"2502.17003","repositories_listed":0,"syntology":null},{"url":null,"slug":"low-rank-and-sparse-model-merging-for-multi","title":"Low-Rank and Sparse Model Merging for Multi-Lingual Speech Recognition and Translation","date":"2025-02-24","arxiv_id":"2502.17380","repositories_listed":0,"syntology":null},{"url":"/paper/sfld-reducing-the-content-bias-for-ai","slug":"sfld-reducing-the-content-bias-for-ai","title":"SFLD: Reducing the content bias for AI-generated Image Detection","date":"2025-02-24","arxiv_id":"2502.17105","repositories_listed":0,"syntology":null},{"url":null,"slug":"urdullama-1-0-dataset-curation-preprocessing","title":"UrduLLaMA 1.0: Dataset Curation, Preprocessing, and Evaluation in Low-Resource Settings","date":"2025-02-24","arxiv_id":"2502.16961","repositories_listed":0,"syntology":null},{"url":null,"slug":"be-a-multitude-to-itself-a-prompt-evolution","title":"Be a Multitude to Itself: A Prompt Evolution Framework for Red Teaming","date":"2025-02-22","arxiv_id":"2502.16109","repositories_listed":0,"syntology":null},{"url":null,"slug":"esans-effective-and-semantic-aware-negative","title":"ESANS: Effective and Semantic-Aware Negative Sampling for Large-Scale Retrieval Systems","date":"2025-02-22","arxiv_id":"2502.16077","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-objective-cat-swarm-optimization","title":"Multi-objective Cat Swarm Optimization Algorithm based on a Grid System","date":"2025-02-22","arxiv_id":"2502.19439","repositories_listed":0,"syntology":null},{"url":null,"slug":"chitrarth-bridging-vision-and-language-for-a","title":"Chitrarth: Bridging Vision and Language for a Billion People","date":"2025-02-21","arxiv_id":"2502.15392","repositories_listed":0,"syntology":null},{"url":null,"slug":"mmrag-multi-mode-retrieval-augmented","title":"MMRAG: Multi-Mode Retrieval-Augmented Generation with Large Language Models for Biomedical In-Context Learning","date":"2025-02-21","arxiv_id":"2502.15954","repositories_listed":0,"syntology":null},{"url":null,"slug":"moma-a-modular-deep-learning-framework-for","title":"MoMa: A Modular Deep Learning Framework for Material Property Prediction","date":"2025-02-21","arxiv_id":"2502.15483","repositories_listed":0,"syntology":null},{"url":null,"slug":"non-linear-flow-matching-for-full-atom","title":"Non-Linear Flow Matching for Full-Atom Peptide Design","date":"2025-02-21","arxiv_id":"2502.15855","repositories_listed":0,"syntology":null},{"url":null,"slug":"strategic-priorities-for-transformative","title":"Strategic priorities for transformative progress in advancing biology with proteomics and artificial intelligence","date":"2025-02-21","arxiv_id":"2502.15867","repositories_listed":0,"syntology":null},{"url":null,"slug":"unveiling-attractor-cycles-in-large-language","title":"Unveiling Attractor Cycles in Large Language Models: A Dynamical Systems View of Successive Paraphrasing","date":"2025-02-21","arxiv_id":"2502.15208","repositories_listed":0,"syntology":null},{"url":null,"slug":"affinity-and-diversity-a-unified-metric-for","title":"Affinity and Diversity: A Unified Metric for Demonstration Selection via Internal Representations","date":"2025-02-20","arxiv_id":"2502.14380","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-enhancement-of-jiang-z-et-al-s-compression","title":"An Enhancement of Jiang, Z., et al.s Compression-Based Classification Algorithm Applied to News Article Categorization","date":"2025-02-20","arxiv_id":"2502.14444","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-advanced-techniques-for-visual","title":"Exploring Advanced Techniques for Visual Question Answering: A Comprehensive Comparison","date":"2025-02-20","arxiv_id":"2502.14827","repositories_listed":0,"syntology":null},{"url":null,"slug":"reducing-false-positives-in-strong-lens","title":"Reducing false positives in strong lens detection through effective augmentation and ensemble learning","date":"2025-02-20","arxiv_id":"2502.14936","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-large-and-balanced-corpus-for-fine-grained","title":"A Large and Balanced Corpus for Fine-grained Arabic Readability Assessment","date":"2025-02-19","arxiv_id":"2502.13520","repositories_listed":0,"syntology":null},{"url":null,"slug":"diffexp-efficient-exploration-in-reward-fine","title":"DiffExp: Efficient Exploration in Reward Fine-tuning for Text-to-Image Diffusion Models","date":"2025-02-19","arxiv_id":"2502.14070","repositories_listed":0,"syntology":null},{"url":null,"slug":"diffsampling-enhancing-diversity-and-accuracy","title":"DiffSampling: Enhancing Diversity and Accuracy in Neural Text Generation","date":"2025-02-19","arxiv_id":"2502.14037","repositories_listed":0,"syntology":null},{"url":null,"slug":"diversity-driven-data-selection-for-language","title":"Diversity-driven Data Selection for Language Model Tuning through Sparse Autoencoder","date":"2025-02-19","arxiv_id":"2502.14050","repositories_listed":0,"syntology":null},{"url":"/paper/fragfm-efficient-fragment-based-molecular","slug":"fragfm-efficient-fragment-based-molecular","title":"FragFM: Hierarchical Framework for Efficient Molecule Generation via Fragment-Level Discrete Flow Matching","date":"2025-02-19","arxiv_id":"2502.15805","repositories_listed":0,"syntology":{"n":14,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":6,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":2,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 6 unverified","sample_list":"/paper/fragfm-efficient-fragment-based-molecular#ran","syntology_url":"https://syntology.ai/paper/2502.15805","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2502.15805"}},"official":null}},{"url":null,"slug":"image-compositing-is-all-you-need-for-data","title":"Image compositing is all you need for data augmentation","date":"2025-02-19","arxiv_id":"2502.13936","repositories_listed":0,"syntology":null},{"url":null,"slug":"mixed-signals-a-diverse-point-cloud-dataset","title":"Mixed Signals: A Diverse Point Cloud Dataset for Heterogeneous LiDAR V2X Collaboration","date":"2025-02-19","arxiv_id":"2502.14156","repositories_listed":0,"syntology":null},{"url":null,"slug":"vital-a-new-dataset-for-benchmarking","title":"VITAL: A New Dataset for Benchmarking Pluralistic Alignment in Healthcare","date":"2025-02-19","arxiv_id":"2502.13775","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-novelty-improve-the-diversity-and","title":"Multi-Novelty: Improve the Diversity and Novelty of Contents Generated by Large Language Models via inference-time Multi-Views Brainstorming","date":"2025-02-18","arxiv_id":"2502.12700","repositories_listed":0,"syntology":null},{"url":null,"slug":"thinking-outside-the-gray-box-a-context-based","title":"Thinking Outside the (Gray) Box: A Context-Based Score for Assessing Value and Originality in Neural Text Generation","date":"2025-02-18","arxiv_id":"2502.13207","repositories_listed":0,"syntology":null},{"url":null,"slug":"understanding-and-evaluating-hallucinations","title":"Understanding and Evaluating Hallucinations in 3D Visual Language Models","date":"2025-02-18","arxiv_id":"2502.15888","repositories_listed":0,"syntology":null},{"url":null,"slug":"demographic-attributes-prediction-from-speech","title":"Demographic Attributes Prediction from Speech Using WavLM Embeddings","date":"2025-02-17","arxiv_id":"2502.12007","repositories_listed":0,"syntology":null},{"url":null,"slug":"diversity-oriented-data-augmentation-with","title":"Diversity-Oriented Data Augmentation with Large Language Models","date":"2025-02-17","arxiv_id":"2502.11671","repositories_listed":0,"syntology":null},{"url":null,"slug":"energy-conscious-llm-decoding-impact-of-text","title":"Energy-Conscious LLM Decoding: Impact of Text Generation Strategies on GPU Energy Consumption","date":"2025-02-17","arxiv_id":"2502.11723","repositories_listed":0,"syntology":null},{"url":null,"slug":"is-human-like-text-liked-by-humans","title":"Is Human-Like Text Liked by Humans? Multilingual Human Detection and Preference Against AI","date":"2025-02-17","arxiv_id":"2502.11614","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-computational-tractability-of-the-many","title":"On the Computational Tractability of the (Many) Shapley Values","date":"2025-02-17","arxiv_id":"2502.12295","repositories_listed":0,"syntology":null},{"url":null,"slug":"diversified-sampling-improves-scaling-llm","title":"Diversified Sampling Improves Scaling LLM inference","date":"2025-02-16","arxiv_id":"2502.11027","repositories_listed":0,"syntology":null},{"url":null,"slug":"understanding-dynamic-diffusion-process-of","title":"Attention Mechanism for LLM-based Agents Dynamic Diffusion under Information Asymmetry","date":"2025-02-16","arxiv_id":"2502.13160","repositories_listed":0,"syntology":null},{"url":null,"slug":"vendi-rag-adaptively-trading-off-diversity","title":"Vendi-RAG: Adaptively Trading-Off Diversity And Quality Significantly Improves Retrieval Augmented Generation With LLMs","date":"2025-02-16","arxiv_id":"2502.11228","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-vendiscope-an-algorithmic-microscope-for","title":"The Vendiscope: An Algorithmic Microscope For Data Collections","date":"2025-02-15","arxiv_id":"2502.10828","repositories_listed":0,"syntology":null},{"url":null,"slug":"to-bin-or-not-to-bin-alternative","title":"To Bin or not to Bin: Alternative Representations of Mass Spectra","date":"2025-02-15","arxiv_id":"2502.10851","repositories_listed":0,"syntology":null},{"url":null,"slug":"direct-preference-optimization-enhanced-multi","title":"Direct Preference Optimization-Enhanced Multi-Guided Diffusion Model for Traffic Scenario Generation","date":"2025-02-14","arxiv_id":"2502.12178","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-age-related-robustness-in-children","title":"Enhancing Age-Related Robustness in Children Speaker Verification","date":"2025-02-14","arxiv_id":"2502.10511","repositories_listed":0,"syntology":null},{"url":null,"slug":"expert-agnostic-learning-to-defer","title":"Expert-Agnostic Learning to Defer","date":"2025-02-14","arxiv_id":"2502.10533","repositories_listed":0,"syntology":null},{"url":null,"slug":"communication-is-all-you-need-persuasion","title":"Communication is All You Need: Persuasion Dataset Construction via Multi-LLM Communication","date":"2025-02-13","arxiv_id":"2502.08896","repositories_listed":0,"syntology":null},{"url":null,"slug":"diversity-enhances-an-llm-s-performance-in","title":"Diversity Enhances an LLM's Performance in RAG and Long-context Task","date":"2025-02-13","arxiv_id":"2502.09017","repositories_listed":0,"syntology":null},{"url":null,"slug":"inverse-problems-with-experiment-guided","title":"Inverse problems with experiment-guided AlphaFold","date":"2025-02-13","arxiv_id":"2502.09372","repositories_listed":0,"syntology":null},{"url":null,"slug":"matina-a-large-scale-73b-token-persian-text","title":"Matina: A Large-Scale 73B Token Persian Text Corpus","date":"2025-02-13","arxiv_id":"2502.09188","repositories_listed":0,"syntology":null},{"url":"/paper/when-and-how-does-clip-enable-domain-and","slug":"when-and-how-does-clip-enable-domain-and","title":"When and How Does CLIP Enable Domain and Compositional Generalization?","date":"2025-02-13","arxiv_id":"2502.09507","repositories_listed":0,"syntology":{"n":32,"n_ran":24,"n_constructed":0,"n_ran_checked":16,"n_instrument":8,"n_unverified":8,"n_honours":0,"n_violates":0,"n_no_contract":16,"n_pointer_only":5,"phrase":"24 ran (of which 0 constructed an object rather than computing a result; 16 with no instrument failure: 0 honoured, 0 violated, 16 with no contract checked; 8 where Syntology's instrument failed) · 8 unverified","sample_list":"/paper/when-and-how-does-clip-enable-domain-and#ran","syntology_url":"https://syntology.ai/paper/2502.09507","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2502.09507"}},"official":null}},{"url":null,"slug":"genias-generator-for-instantiating-anomalies","title":"GenIAS: Generator for Instantiating Anomalies in time Series","date":"2025-02-12","arxiv_id":"2502.08262","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-paradox-of-stochasticity-limited","title":"The Paradox of Stochasticity: Limited Creativity and Computational Decoupling in Temperature-Varied LLM Outputs of Structured Fictional Data","date":"2025-02-12","arxiv_id":"2502.08515","repositories_listed":0,"syntology":null},{"url":null,"slug":"classifier-free-guidance-from-high","title":"Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms","date":"2025-02-11","arxiv_id":"2502.07849","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-properties-driving-diversity-index","title":"On properties driving diversity index selection","date":"2025-02-11","arxiv_id":"2502.07426","repositories_listed":0,"syntology":null},{"url":null,"slug":"renderbox-expressive-performance-rendering","title":"RenderBox: Expressive Performance Rendering with Text Control","date":"2025-02-11","arxiv_id":"2502.07711","repositories_listed":0,"syntology":null},{"url":null,"slug":"scaling-pre-training-to-one-hundred-billion","title":"Scaling Pre-training to One Hundred Billion Data for Vision Language Models","date":"2025-02-11","arxiv_id":"2502.07617","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-translation-of-emergent","title":"Unsupervised Translation of Emergent Communication","date":"2025-02-11","arxiv_id":"2502.07552","repositories_listed":0,"syntology":null},{"url":null,"slug":"we-can-t-understand-ai-using-our-existing","title":"We Can't Understand AI Using our Existing Vocabulary","date":"2025-02-11","arxiv_id":"2502.07586","repositories_listed":0,"syntology":null},{"url":null,"slug":"extract-qd-framework-a-generic-approach-for","title":"Extract-QD Framework: A Generic Approach for Quality-Diversity in Noisy, Stochastic or Uncertain Domains","date":"2025-02-10","arxiv_id":"2502.06585","repositories_listed":0,"syntology":null},{"url":null,"slug":"many-task-federated-fine-tuning-via-unified","title":"Many-Task Federated Fine-Tuning via Unified Task Vectors","date":"2025-02-10","arxiv_id":"2502.06376","repositories_listed":0,"syntology":null},{"url":null,"slug":"scalable-and-ethical-insider-threat-detection","title":"Scalable and Ethical Insider Threat Detection through Data Synthesis and Analysis by LLMs","date":"2025-02-10","arxiv_id":"2502.07045","repositories_listed":0,"syntology":null},{"url":null,"slug":"select-before-act-spatially-decoupled-action","title":"Select before Act: Spatially Decoupled Action Repetition for Continuous Control","date":"2025-02-10","arxiv_id":"2502.06919","repositories_listed":0,"syntology":null},{"url":null,"slug":"tangled-generating-3d-hair-strands-from","title":"TANGLED: Generating 3D Hair Strands from Images with Arbitrary Styles and Viewpoints","date":"2025-02-10","arxiv_id":"2502.06392","repositories_listed":0,"syntology":null},{"url":null,"slug":"universal-point-spread-function-engineering","title":"Universal point spread function engineering for 3D optical information processing","date":"2025-02-09","arxiv_id":"2502.06025","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-tutorial-on-intersectionality-in-fair","title":"A Tutorial On Intersectionality in Fair Rankings","date":"2025-02-07","arxiv_id":"2502.05333","repositories_listed":0,"syntology":null},{"url":null,"slug":"affine-frequency-division-multiplexing","title":"Affine Frequency Division Multiplexing: Extending OFDM for Scenario-Flexibility and Resilience","date":"2025-02-07","arxiv_id":"2502.04735","repositories_listed":0,"syntology":null},{"url":null,"slug":"ccs-controllable-and-constrained-sampling","title":"CCS: Controllable and Constrained Sampling with Diffusion Models via Initial Noise Perturbation","date":"2025-02-07","arxiv_id":"2502.04670","repositories_listed":0,"syntology":null},{"url":null,"slug":"elite-enhanced-language-image-toxicity","title":"ELITE: Enhanced Language-Image Toxicity Evaluation for Safety","date":"2025-02-07","arxiv_id":"2502.04757","repositories_listed":0,"syntology":null},{"url":null,"slug":"hummingbird-high-fidelity-image-generation","title":"Hummingbird: High Fidelity Image Generation via Multimodal Context Alignment","date":"2025-02-07","arxiv_id":"2502.05153","repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-band-diversity-for-feature","title":"Leveraging band diversity for feature selection in EO data","date":"2025-02-07","arxiv_id":"2502.04713","repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-hypernetworks-and-learnable","title":"Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types","date":"2025-02-07","arxiv_id":"2502.05104","repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-pre-trained-models-for-multimodal","title":"Leveraging Pre-Trained Models for Multimodal Class-Incremental Learning under Adaptive Fusion","date":"2025-02-07","arxiv_id":"2506.09999","repositories_listed":0,"syntology":null},{"url":null,"slug":"poi-pixel-of-interest-for-novel-view","title":"PoI: Pixel of Interest for Novel View Synthesis Assisted Scene Coordinate Regression","date":"2025-02-07","arxiv_id":"2502.04843","repositories_listed":0,"syntology":null},{"url":null,"slug":"seasonal-station-keeping-of-short-duration","title":"Seasonal Station-Keeping of Short Duration High Altitude Balloons using Deep Reinforcement Learning","date":"2025-02-07","arxiv_id":"2502.05014","repositories_listed":0,"syntology":null},{"url":null,"slug":"sedi-instruct-enhancing-alignment-of-language","title":"SeDi-Instruct: Enhancing Alignment of Language Models through Self-Directed Instruction Generation","date":"2025-02-07","arxiv_id":"2502.04774","repositories_listed":0,"syntology":null},{"url":null,"slug":"augmented-conditioning-is-enough-for","title":"Augmented Conditioning Is Enough For Effective Training Image Generation","date":"2025-02-06","arxiv_id":"2502.04475","repositories_listed":0,"syntology":null},{"url":null,"slug":"ditar-diffusion-transformer-autoregressive","title":"DiTAR: Diffusion Transformer Autoregressive Modeling for Speech Generation","date":"2025-02-06","arxiv_id":"2502.03930","repositories_listed":0,"syntology":null}],"record_sha256":"a23a6cb314bab7da85ac265c8d1853d7f326a22fc55af7c57ac64d616f703291","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}