{"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/3","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":3,"pages_in_order":375,"rows_per_page":100,"rows":[201,300],"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/2","next":"/method/softmax/papers/4","papers":[{"paper":null,"slug":"facelivt-face-recognition-using-linear-vision","title":"FaceLiVT: Face Recognition using Linear Vision Transformer with Structural Reparameterization For Mobile Device","date":"2025-06-12","arxiv_id":"2506.10361","n_code_links":0,"syntology":null},{"paper":null,"slug":"fine-grained-perturbation-guidance-via","title":"Fine-Grained Perturbation Guidance via Attention Head Selection","date":"2025-06-12","arxiv_id":"2506.10978","n_code_links":0,"syntology":null},{"paper":null,"slug":"flick-few-labels-text-classification-using-k","title":"Flick: Few Labels Text Classification using K-Aware Intermediate Learning in Multi-Task Low-Resource Languages","date":"2025-06-12","arxiv_id":"2506.10292","n_code_links":0,"syntology":null},{"paper":"/paper/fsatfusion-frequency-spatial-attention","slug":"fsatfusion-frequency-spatial-attention","title":"FSATFusion: Frequency-Spatial Attention Transformer for Infrared and Visible Image Fusion","date":"2025-06-12","arxiv_id":"2506.10366","n_code_links":1,"syntology":null},{"paper":null,"slug":"heterogeneous-irs-assisted-mimo-systems","title":"Heterogeneous-IRS-Assisted MIMO Systems: Channel Estimation and Beamforming","date":"2025-06-12","arxiv_id":"2506.10350","n_code_links":0,"syntology":null},{"paper":null,"slug":"hybiomass-global-hyperspectral-imagery","title":"HyBiomass: Global Hyperspectral Imagery Benchmark Dataset for Evaluating Geospatial Foundation Models in Forest Aboveground Biomass Estimation","date":"2025-06-12","arxiv_id":"2506.11314","n_code_links":0,"syntology":null},{"paper":null,"slug":"improving-medical-visual-representation","title":"Improving Medical Visual Representation Learning with Pathological-level Cross-Modal Alignment and Correlation Exploration","date":"2025-06-12","arxiv_id":"2506.10573","n_code_links":0,"syntology":null},{"paper":null,"slug":"j-ddl-surface-damage-detection-and","title":"J-DDL: Surface Damage Detection and Localization System for Fighter Aircraft","date":"2025-06-12","arxiv_id":"2506.10505","n_code_links":0,"syntology":null},{"paper":"/paper/lightkg-efficient-knowledge-aware","slug":"lightkg-efficient-knowledge-aware","title":"LightKG: Efficient Knowledge-Aware Recommendations with Simplified GNN Architecture","date":"2025-06-12","arxiv_id":"2506.10347","n_code_links":1,"syntology":null},{"paper":null,"slug":"mf2summ-multimodal-fusion-for-video","title":"MF2Summ: Multimodal Fusion for Video Summarization with Temporal Alignment","date":"2025-06-12","arxiv_id":"2506.10430","n_code_links":0,"syntology":null},{"paper":"/paper/mstar-box-free-multi-query-scene-text","slug":"mstar-box-free-multi-query-scene-text","title":"MSTAR: Box-free Multi-query Scene Text Retrieval with Attention Recycling","date":"2025-06-12","arxiv_id":"2506.10609","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":0,"n_instrument":2,"unverified":0,"pointer_only":2,"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":["yingift/mstar"],"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":"/paper/neuralnexus-at-bea-2025-shared-task-retrieval","slug":"neuralnexus-at-bea-2025-shared-task-retrieval","title":"NeuralNexus at BEA 2025 Shared Task: Retrieval-Augmented Prompting for Mistake Identification in AI Tutors","date":"2025-06-12","arxiv_id":"2506.10627","n_code_links":1,"syntology":null},{"paper":null,"slug":"non-stationary-online-learning-for-curved","title":"Non-stationary Online Learning for Curved Losses: Improved Dynamic Regret via Mixability","date":"2025-06-12","arxiv_id":"2506.10616","n_code_links":0,"syntology":null},{"paper":"/paper/pipvit-patch-based-visual-interpretable","slug":"pipvit-patch-based-visual-interpretable","title":"PiPViT: Patch-based Visual Interpretable Prototypes for Retinal Image Analysis","date":"2025-06-12","arxiv_id":"2506.10669","n_code_links":1,"syntology":null},{"paper":null,"slug":"reasoning-rag-via-system-1-or-system-2-a","title":"Reasoning RAG via System 1 or System 2: A Survey on Reasoning Agentic Retrieval-Augmented Generation for Industry Challenges","date":"2025-06-12","arxiv_id":"2506.10408","n_code_links":0,"syntology":null},{"paper":null,"slug":"rethinking-random-masking-in-self","title":"Rethinking Random Masking in Self Distillation on ViT","date":"2025-06-12","arxiv_id":"2506.10582","n_code_links":0,"syntology":null},{"paper":null,"slug":"scenecompleter-dense-3d-scene-completion-for","title":"SceneCompleter: Dense 3D Scene Completion for Generative Novel View Synthesis","date":"2025-06-12","arxiv_id":"2506.10981","n_code_links":0,"syntology":null},{"paper":null,"slug":"semantic-localization-guiding-segment","title":"Semantic Localization Guiding Segment Anything Model For Reference Remote Sensing Image Segmentation","date":"2025-06-12","arxiv_id":"2506.10503","n_code_links":0,"syntology":null},{"paper":null,"slug":"sequential-parallel-duality-in-prefix","title":"Sequential-Parallel Duality in Prefix Scannable Models","date":"2025-06-12","arxiv_id":"2506.10918","n_code_links":0,"syntology":null},{"paper":null,"slug":"slick-selective-localization-and-instance","title":"SLICK: Selective Localization and Instance Calibration for Knowledge-Enhanced Car Damage Segmentation in Automotive Insurance","date":"2025-06-12","arxiv_id":"2506.10528","n_code_links":0,"syntology":null},{"paper":null,"slug":"spectralar-spectral-autoregressive-visual","title":"SpectralAR: Spectral Autoregressive Visual Generation","date":"2025-06-12","arxiv_id":"2506.10962","n_code_links":0,"syntology":null},{"paper":null,"slug":"spelling-out-is-not-straightforward-llms","title":"Spelling-out is not Straightforward: LLMs' Capability of Tokenization from Token to Characters","date":"2025-06-12","arxiv_id":"2506.10641","n_code_links":0,"syntology":null},{"paper":"/paper/swe-factory-your-automated-factory-for-issue","slug":"swe-factory-your-automated-factory-for-issue","title":"SWE-Factory: Your Automated Factory for Issue Resolution Training Data and Evaluation Benchmarks","date":"2025-06-12","arxiv_id":"2506.10954","n_code_links":1,"syntology":null},{"paper":"/paper/tablerag-a-retrieval-augmented-generation","slug":"tablerag-a-retrieval-augmented-generation","title":"TableRAG: A Retrieval Augmented Generation Framework for Heterogeneous Document Reasoning","date":"2025-06-12","arxiv_id":"2506.10380","n_code_links":1,"syntology":null},{"paper":null,"slug":"the-role-of-generative-ai-in-facilitating","title":"The Role of Generative AI in Facilitating Social Interactions: A Scoping Review","date":"2025-06-12","arxiv_id":"2506.10927","n_code_links":0,"syntology":null},{"paper":"/paper/think-before-you-simulate-symbolic-reasoning-1","slug":"think-before-you-simulate-symbolic-reasoning-1","title":"Think before You Simulate: Symbolic Reasoning to Orchestrate Neural Computation for Counterfactual Question Answering","date":"2025-06-12","arxiv_id":"2506.10753","n_code_links":1,"syntology":null},{"paper":"/paper/towards-robust-multimodal-emotion-recognition","slug":"towards-robust-multimodal-emotion-recognition","title":"Towards Robust Multimodal Emotion Recognition under Missing Modalities and Distribution Shifts","date":"2025-06-12","arxiv_id":"2506.10452","n_code_links":1,"syntology":null},{"paper":"/paper/towards-understanding-bias-in-synthetic-data","slug":"towards-understanding-bias-in-synthetic-data","title":"Towards Understanding Bias in Synthetic Data for Evaluation","date":"2025-06-12","arxiv_id":"2506.10301","n_code_links":1,"syntology":null},{"paper":"/paper/2506-10174","slug":"2506-10174","title":"Retrieval of Surface Solar Radiation through Implicit Albedo Recovery from Temporal Context","date":"2025-06-11","arxiv_id":"2506.10174","n_code_links":1,"syntology":null},{"paper":null,"slug":"2506-10225","title":"Fine-Grained control over Music Generation with Activation Steering","date":"2025-06-11","arxiv_id":"2506.10225","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-new-type-of-federated-clustering-a-non","title":"A new type of federated clustering: A non-model-sharing approach","date":"2025-06-11","arxiv_id":"2506.10244","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-novel-lightweight-transformer-with-edge","title":"A Novel Lightweight Transformer with Edge-Aware Fusion for Remote Sensing Image Captioning","date":"2025-06-11","arxiv_id":"2506.09429","n_code_links":0,"syntology":null},{"paper":null,"slug":"analysis-of-anonymous-user-interaction","title":"Analysis of Anonymous User Interaction Relationships and Prediction of Advertising Feedback Based on Graph Neural Network","date":"2025-06-11","arxiv_id":"2506.13787","n_code_links":0,"syntology":null},{"paper":"/paper/attention-please-revisiting-attentive-probing","slug":"attention-please-revisiting-attentive-probing","title":"Attention, Please! Revisiting Attentive Probing for Masked Image Modeling","date":"2025-06-11","arxiv_id":"2506.10178","n_code_links":1,"syntology":null},{"paper":null,"slug":"auto-compressing-networks","title":"Auto-Compressing Networks","date":"2025-06-11","arxiv_id":"2506.09714","n_code_links":0,"syntology":null},{"paper":null,"slug":"can-llms-generate-good-stories-insights-and","title":"Can LLMs Generate Good Stories? Insights and Challenges from a Narrative Planning Perspective","date":"2025-06-11","arxiv_id":"2506.10161","n_code_links":0,"syntology":null},{"paper":null,"slug":"deteccao-da-psoriase-utilizando-visao","title":"Detecção da Psoríase Utilizando Visão Computacional: Uma Abordagem Comparativa Entre CNNs e Vision Transformers","date":"2025-06-11","arxiv_id":"2506.10119","n_code_links":0,"syntology":null},{"paper":null,"slug":"dgs-lrm-real-time-deformable-3d-gaussian","title":"DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos","date":"2025-06-11","arxiv_id":"2506.09997","n_code_links":0,"syntology":null},{"paper":null,"slug":"elbo-t2ialign-a-generic-elbo-based-method-for","title":"ELBO-T2IAlign: A Generic ELBO-Based Method for Calibrating Pixel-level Text-Image Alignment in Diffusion Models","date":"2025-06-11","arxiv_id":"2506.09740","n_code_links":0,"syntology":null},{"paper":null,"slug":"error-guided-pose-augmentation-enhancing","title":"Error-Guided Pose Augmentation: Enhancing Rehabilitation Exercise Assessment through Targeted Data Generation","date":"2025-06-11","arxiv_id":"2506.09833","n_code_links":0,"syntology":null},{"paper":"/paper/exposure-slot-exposure-centric","slug":"exposure-slot-exposure-centric","title":"Exposure-slot: Exposure-centric representations learning with Slot-in-Slot Attention for Region-aware Exposure Correction","date":"2025-06-11","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"formalizing-neuromorphic-control-systems-a","title":"Formalizing Neuromorphic Control Systems: A General Proposal and A Rhythmic Case Study","date":"2025-06-11","arxiv_id":"2506.10203","n_code_links":0,"syntology":null},{"paper":null,"slug":"from-judgment-to-interference-early-stopping","title":"From Judgment to Interference: Early Stopping LLM Harmful Outputs via Streaming Content Monitoring","date":"2025-06-11","arxiv_id":"2506.09996","n_code_links":0,"syntology":null},{"paper":null,"slug":"generalization-error-analysis-for-attack-free","title":"Generalization Error Analysis for Attack-Free and Byzantine-Resilient Decentralized Learning with Data Heterogeneity","date":"2025-06-11","arxiv_id":"2506.09438","n_code_links":0,"syntology":null},{"paper":null,"slug":"generalizing-supervised-contrastive-learning","title":"Generalizing Supervised Contrastive learning: A Projection Perspective","date":"2025-06-11","arxiv_id":"2506.09810","n_code_links":0,"syntology":null},{"paper":null,"slug":"how-attention-simplifies-mental","title":"How attention simplifies mental representations for planning","date":"2025-06-11","arxiv_id":"2506.09520","n_code_links":0,"syntology":null},{"paper":"/paper/large-language-models-for-toxic-language","slug":"large-language-models-for-toxic-language","title":"Large Language Models for Toxic Language Detection in Low-Resource Balkan Languages","date":"2025-06-11","arxiv_id":"2506.09992","n_code_links":1,"syntology":null},{"paper":null,"slug":"latent-multi-head-attention-for-small","title":"Latent Multi-Head Attention for Small Language Models","date":"2025-06-11","arxiv_id":"2506.09342","n_code_links":0,"syntology":null},{"paper":"/paper/learning-efficient-and-generalizable-graph","slug":"learning-efficient-and-generalizable-graph","title":"Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering","date":"2025-06-11","arxiv_id":"2506.09645","n_code_links":1,"syntology":null},{"paper":null,"slug":"learning-to-optimize-package-picking-for","title":"Learning to Optimize Package Picking for Large-Scale, Real-World Robot Induction","date":"2025-06-11","arxiv_id":"2506.09765","n_code_links":0,"syntology":null},{"paper":"/paper/llm-powered-cpi-prediction-inference-with","slug":"llm-powered-cpi-prediction-inference-with","title":"LLM-Powered CPI Prediction Inference with Online Text Time Series","date":"2025-06-11","arxiv_id":"2506.09516","n_code_links":1,"syntology":null},{"paper":"/paper/marrying-autoregressive-transformer-and","slug":"marrying-autoregressive-transformer-and","title":"Marrying Autoregressive Transformer and Diffusion with Multi-Reference Autoregression","date":"2025-06-11","arxiv_id":"2506.09482","n_code_links":1,"syntology":null},{"paper":null,"slug":"measuring-corporate-human-capital-disclosures","title":"Measuring Corporate Human Capital Disclosures: Lexicon, Data, Code, and Research Opportunities","date":"2025-06-11","arxiv_id":"2506.10155","n_code_links":0,"syntology":null},{"paper":null,"slug":"multiverse-your-language-models-secretly","title":"Multiverse: Your Language Models Secretly Decide How to Parallelize and Merge Generation","date":"2025-06-11","arxiv_id":"2506.09991","n_code_links":0,"syntology":null},{"paper":"/paper/mutual-supervised-learning-for-sequential-to","slug":"mutual-supervised-learning-for-sequential-to","title":"Mutual-Supervised Learning for Sequential-to-Parallel Code Translation","date":"2025-06-11","arxiv_id":"2506.11153","n_code_links":1,"syntology":null},{"paper":"/paper/on-the-fly-adaptive-distillation-of","slug":"on-the-fly-adaptive-distillation-of","title":"On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention","date":"2025-06-11","arxiv_id":"2506.09316","n_code_links":1,"syntology":null},{"paper":null,"slug":"q-sam2-accurate-quantization-for-segment","title":"Q-SAM2: Accurate Quantization for Segment Anything Model 2","date":"2025-06-11","arxiv_id":"2506.09782","n_code_links":0,"syntology":null},{"paper":"/paper/query-focused-retrieval-heads-improve-long","slug":"query-focused-retrieval-heads-improve-long","title":"Query-Focused Retrieval Heads Improve Long-Context Reasoning and Re-ranking","date":"2025-06-11","arxiv_id":"2506.09944","n_code_links":1,"syntology":{"ran":16,"of":18,"n_ran_checked":11,"n_instrument":5,"unverified":2,"pointer_only":0,"phrase":"16 ran (of which 0 constructed an object rather than computing a result; 11 with no instrument failure: 0 honoured, 0 violated, 11 with no contract checked; 5 where Syntology's instrument failed) · 2 unverified","official":{"repos":["princeton-pli/qrhead"],"state":"official (archive's flag): 16 ran","n_ran":16,"n_constructed":0,"n_ran_no_instrument_failure":11,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"sparsessm-efficient-selective-structured","title":"SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot","date":"2025-06-11","arxiv_id":"2506.09613","n_code_links":0,"syntology":null},{"paper":"/paper/survival-analysis-as-imprecise-classification","slug":"survival-analysis-as-imprecise-classification","title":"Survival Analysis as Imprecise Classification with Trainable Kernels","date":"2025-06-11","arxiv_id":"2506.10140","n_code_links":1,"syntology":null},{"paper":null,"slug":"synergizing-reinforcement-learning-and","title":"Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization","date":"2025-06-11","arxiv_id":"2506.09404","n_code_links":0,"syntology":null},{"paper":null,"slug":"towards-bridging-the-reward-generation-gap-in","title":"Towards Bridging the Reward-Generation Gap in Direct Alignment Algorithms","date":"2025-06-11","arxiv_id":"2506.09457","n_code_links":0,"syntology":null},{"paper":null,"slug":"transxssm-a-hybrid-transformer-state-space","title":"TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding","date":"2025-06-11","arxiv_id":"2506.09507","n_code_links":0,"syntology":null},{"paper":null,"slug":"you-are-what-you-say-exploiting-linguistic","title":"You Are What You Say: Exploiting Linguistic Content for VoicePrivacy Attacks","date":"2025-06-11","arxiv_id":"2506.09521","n_code_links":0,"syntology":null},{"paper":null,"slug":"2506-08298","title":"H$^2$GFM: Towards unifying Homogeneity and Heterogeneity on Text-Attributed Graphs","date":"2025-06-10","arxiv_id":"2506.08298","n_code_links":0,"syntology":null},{"paper":"/paper/2506-08357","slug":"2506-08357","title":"MD-ViSCo: A Unified Model for Multi-Directional Vital Sign Waveform Conversion","date":"2025-06-10","arxiv_id":"2506.08357","n_code_links":1,"syntology":null},{"paper":"/paper/2506-08455","slug":"2506-08455","title":"The interplay of robustness and generalization in quantum machine learning","date":"2025-06-10","arxiv_id":"2506.08455","n_code_links":1,"syntology":null},{"paper":null,"slug":"2506-08534","title":"DCD: A Semantic Segmentation Model for Fetal Ultrasound Four-Chamber View","date":"2025-06-10","arxiv_id":"2506.08534","n_code_links":0,"syntology":null},{"paper":"/paper/2506-08600","slug":"2506-08600","title":"CALT: A Library for Computer Algebra with Transformer","date":"2025-06-10","arxiv_id":"2506.08600","n_code_links":1,"syntology":null},{"paper":null,"slug":"2506-08785","title":"POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration","date":"2025-06-10","arxiv_id":"2506.08785","n_code_links":0,"syntology":null},{"paper":"/paper/2506-10030","slug":"2506-10030","title":"Safeguarding Multimodal Knowledge Copyright in the RAG-as-a-Service Environment","date":"2025-06-10","arxiv_id":"2506.10030","n_code_links":1,"syntology":null},{"paper":null,"slug":"2506-10035","title":"FastFLUX: Pruning FLUX with Block-wise Replacement and Sandwich Training","date":"2025-06-10","arxiv_id":"2506.10035","n_code_links":0,"syntology":null},{"paper":null,"slug":"adversarial-attack-safety-alignment-alkali","title":"AdversariaL attacK sAfety aLIgnment(ALKALI): Safeguarding LLMs through GRACE: Geometric Representation-Aware Contrastive Enhancement- Introducing Adversarial Vulnerability Quality Index (AVQI)","date":"2025-06-10","arxiv_id":"2506.08885","n_code_links":0,"syntology":null},{"paper":null,"slug":"arareasoner-evaluating-reasoning-based-llms","title":"AraReasoner: Evaluating Reasoning-Based LLMs for Arabic NLP","date":"2025-06-10","arxiv_id":"2506.08768","n_code_links":0,"syntology":null},{"paper":null,"slug":"atomic-to-compositional-generalization-for","title":"Atomic-to-Compositional Generalization for Mobile Agents with A New Benchmark and Scheduling System","date":"2025-06-10","arxiv_id":"2506.08972","n_code_links":0,"syntology":null},{"paper":null,"slug":"biolangfusion-multimodal-fusion-of-dna-mrna","title":"BioLangFusion: Multimodal Fusion of DNA, mRNA, and Protein Language Models","date":"2025-06-10","arxiv_id":"2506.08936","n_code_links":0,"syntology":null},{"paper":null,"slug":"cc-rag-structured-multi-hop-reasoning-via","title":"CC-RAG: Structured Multi-Hop Reasoning via Theme-Based Causal Graphs","date":"2025-06-10","arxiv_id":"2506.08364","n_code_links":0,"syntology":null},{"paper":null,"slug":"convergence-of-spectral-principal-paths-how","title":"Convergence of Spectral Principal Paths: How Deep Networks Distill Linear Representations from Noisy Inputs","date":"2025-06-10","arxiv_id":"2506.08543","n_code_links":0,"syntology":null},{"paper":"/paper/counselbench-a-large-scale-expert-evaluation","slug":"counselbench-a-large-scale-expert-evaluation","title":"CounselBench: A Large-Scale Expert Evaluation and Adversarial Benchmark of Large Language Models in Mental Health Counseling","date":"2025-06-10","arxiv_id":"2506.08584","n_code_links":1,"syntology":null},{"paper":null,"slug":"deal-disentangling-transformer-head","title":"DEAL: Disentangling Transformer Head Activations for LLM Steering","date":"2025-06-10","arxiv_id":"2506.08359","n_code_links":0,"syntology":null},{"paper":"/paper/draft-based-approximate-inference-for-llms","slug":"draft-based-approximate-inference-for-llms","title":"Draft-based Approximate Inference for LLMs","date":"2025-06-10","arxiv_id":"2506.08373","n_code_links":1,"syntology":{"ran":8,"of":11,"n_ran_checked":3,"n_instrument":5,"unverified":3,"pointer_only":5,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 5 where Syntology's instrument failed) · 3 unverified","official":{"repos":["furiosa-ai/draft-based-approx-llm"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":3,"ran_from_kinds":["official","unlocated"]}}},{"paper":"/paper/dragged-into-conflicts-detecting-and","slug":"dragged-into-conflicts-detecting-and","title":"DRAGged into Conflicts: Detecting and Addressing Conflicting Sources in Search-Augmented LLMs","date":"2025-06-10","arxiv_id":"2506.08500","n_code_links":1,"syntology":null},{"paper":null,"slug":"ecmnet-lightweight-semantic-segmentation-with","title":"ECMNet:Lightweight Semantic Segmentation with Efficient CNN-Mamba Network","date":"2025-06-10","arxiv_id":"2506.08629","n_code_links":0,"syntology":null},{"paper":"/paper/evaluating-llms-across-multi-cognitive-levels","slug":"evaluating-llms-across-multi-cognitive-levels","title":"Evaluating LLMs Across Multi-Cognitive Levels: From Medical Knowledge Mastery to Scenario-Based Problem Solving","date":"2025-06-10","arxiv_id":"2506.08349","n_code_links":1,"syntology":{"ran":3,"of":3,"n_ran_checked":0,"n_instrument":3,"unverified":0,"pointer_only":3,"phrase":"3 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; 3 where Syntology's instrument failed) · 0 unverified","official":{"repos":["thumlp/multicogeval"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/faithfulrag-fact-level-conflict-modeling-for","slug":"faithfulrag-fact-level-conflict-modeling-for","title":"FaithfulRAG: Fact-Level Conflict Modeling for Context-Faithful Retrieval-Augmented Generation","date":"2025-06-10","arxiv_id":"2506.08938","n_code_links":1,"syntology":null},{"paper":"/paper/fedrag-a-framework-for-fine-tuning-retrieval","slug":"fedrag-a-framework-for-fine-tuning-retrieval","title":"FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems","date":"2025-06-10","arxiv_id":"2506.09200","n_code_links":1,"syntology":null},{"paper":null,"slug":"fine-grained-spatially-varying-material","title":"Fine-Grained Spatially Varying Material Selection in Images","date":"2025-06-10","arxiv_id":"2506.09023","n_code_links":0,"syntology":null},{"paper":null,"slug":"floorplanmae-a-self-supervised-framework-for","title":"FloorplanMAE:A self-supervised framework for complete floorplan generation from partial inputs","date":"2025-06-10","arxiv_id":"2506.08363","n_code_links":0,"syntology":null},{"paper":null,"slug":"genetic-transformer-assisted-quantum-neural","title":"Genetic Transformer-Assisted Quantum Neural Networks for Optimal Circuit Design","date":"2025-06-10","arxiv_id":"2506.09205","n_code_links":0,"syntology":null},{"paper":null,"slug":"graph-attention-based-decentralized-actor","title":"Graph Attention-based Decentralized Actor-Critic for Dual-Objective Control of Multi-UAV Swarms","date":"2025-06-10","arxiv_id":"2506.09195","n_code_links":0,"syntology":null},{"paper":null,"slug":"graph-signal-aware-decomposition-of-dynamic","title":"Graph signal aware decomposition of dynamic networks via latent graphs","date":"2025-06-10","arxiv_id":"2506.08519","n_code_links":0,"syntology":null},{"paper":null,"slug":"hgformer-a-hierarchical-graph-transformer","title":"HGFormer: A Hierarchical Graph Transformer Framework for Two-Stage Colonel Blotto Games via Reinforcement Learning","date":"2025-06-10","arxiv_id":"2506.08580","n_code_links":0,"syntology":null},{"paper":null,"slug":"hierarchical-neural-collapse-detection","title":"Hierarchical Neural Collapse Detection Transformer for Class Incremental Object Detection","date":"2025-06-10","arxiv_id":"2506.08562","n_code_links":0,"syntology":null},{"paper":"/paper/hyperspectral-image-classification-via","slug":"hyperspectral-image-classification-via","title":"Hyperspectral Image Classification via Transformer-based Spectral-Spatial Attention Decoupling and Adaptive Gating","date":"2025-06-10","arxiv_id":"2506.08324","n_code_links":1,"syntology":null},{"paper":"/paper/inherently-faithful-attention-maps-for-vision","slug":"inherently-faithful-attention-maps-for-vision","title":"Inherently Faithful Attention Maps for Vision Transformers","date":"2025-06-10","arxiv_id":"2506.08915","n_code_links":1,"syntology":null},{"paper":"/paper/joformer-journey-based-transformer-theory-and","slug":"joformer-journey-based-transformer-theory-and","title":"JoFormer (Journey-based Transformer): Theory and Empirical Analysis on the Tiny Shakespeare Dataset","date":"2025-06-10","arxiv_id":"2506.08652","n_code_links":1,"syntology":null},{"paper":"/paper/ladcast-a-latent-diffusion-model-for-medium","slug":"ladcast-a-latent-diffusion-model-for-medium","title":"LaDCast: A Latent Diffusion Model for Medium-Range Ensemble Weather Forecasting","date":"2025-06-10","arxiv_id":"2506.09193","n_code_links":1,"syntology":null},{"paper":"/paper/learnable-spatial-temporal-positional","slug":"learnable-spatial-temporal-positional","title":"Learnable Spatial-Temporal Positional Encoding for Link Prediction","date":"2025-06-10","arxiv_id":"2506.08309","n_code_links":1,"syntology":{"ran":5,"of":5,"n_ran_checked":5,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"5 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; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["kthrn22/l-step"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"liftvsr-lifting-image-diffusion-to-video","title":"LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\\times$RTX 4090s","date":"2025-06-10","arxiv_id":"2506.08529","n_code_links":0,"syntology":null},{"paper":"/paper/mac-an-efficient-gradient-preconditioning","slug":"mac-an-efficient-gradient-preconditioning","title":"MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature","date":"2025-06-10","arxiv_id":"2506.08464","n_code_links":1,"syntology":null}],"record_sha256":"0528c02851532d834de39c447853a864bfbe4b61481c14a3f2cb347c839bf31a","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}