{"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/retrieval/papers/66","list_of":"/task/retrieval","task":"Retrieval","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":66,"pages_in_order":143,"rows_per_page":100,"rows":[6501,6600],"of":14297,"counts":{"archive_papers_tagged":14297,"with_a_code_link":5274,"where_syntology_ran_a_sample":1303,"not_listed_spam_title":0,"listed":14297,"listed_where_code_ran":1303,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":1067,"every_run_a_failure_of_syntologys_instrument":236,"listed_with_a_run_with_no_instrument_failure":1067,"listed_every_run_a_failure_of_syntologys_instrument":236,"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/retrieval","prev":"/task/retrieval/papers/65","next":"/task/retrieval/papers/67","papers":[{"url":null,"slug":"a-diffuse-light-field-imaging-model-for","title":"A Diffuse Light Field Imaging Model for Forward-Scattering Photon-Coded Signal Retrieval","date":"2024-11-10","arxiv_id":"2411.06357","repositories_listed":0,"syntology":null},{"url":null,"slug":"lprotector-an-llm-driven-vulnerability","title":"LProtector: An LLM-driven Vulnerability Detection System","date":"2024-11-10","arxiv_id":"2411.06493","repositories_listed":0,"syntology":null},{"url":null,"slug":"building-an-efficient-multilingual-non-profit","title":"Building an Efficient Multilingual Non-Profit IR System for the Islamic Domain Leveraging Multiprocessing Design in Rust","date":"2024-11-09","arxiv_id":"2411.06151","repositories_listed":0,"syntology":null},{"url":null,"slug":"clustering-algorithms-and-rag-enhancing-semi","title":"Clustering Algorithms and RAG Enhancing Semi-Supervised Text Classification with Large LLMs","date":"2024-11-09","arxiv_id":"2411.06175","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-knowledge-boundaries-in-large","title":"Exploring Knowledge Boundaries in Large Language Models for Retrieval Judgment","date":"2024-11-09","arxiv_id":"2411.06207","repositories_listed":0,"syntology":null},{"url":null,"slug":"keyb2-selecting-key-blocks-is-also-important","title":"KeyB2: Selecting Key Blocks is Also Important for Long Document Ranking with Large Language Models","date":"2024-11-09","arxiv_id":"2411.06254","repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-retrieval-augmented-generation-for-1","title":"Leveraging Retrieval-Augmented Generation for Persian University Knowledge Retrieval","date":"2024-11-09","arxiv_id":"2411.06237","repositories_listed":0,"syntology":null},{"url":null,"slug":"m-longdoc-a-benchmark-for-multimodal-super","title":"M-Longdoc: A Benchmark For Multimodal Super-Long Document Understanding And A Retrieval-Aware Tuning Framework","date":"2024-11-09","arxiv_id":"2411.06176","repositories_listed":0,"syntology":null},{"url":null,"slug":"sufficient-context-a-new-lens-on-retrieval","title":"Sufficient Context: A New Lens on Retrieval Augmented Generation Systems","date":"2024-11-09","arxiv_id":"2411.06037","repositories_listed":0,"syntology":null},{"url":null,"slug":"toursynbio-search-a-large-language-model","title":"TourSynbio-Search: A Large Language Model Driven Agent Framework for Unified Search Method for Protein Engineering","date":"2024-11-09","arxiv_id":"2411.06024","repositories_listed":0,"syntology":null},{"url":null,"slug":"assessing-the-answerability-of-queries-in","title":"Assessing the Answerability of Queries in Retrieval-Augmented Code Generation","date":"2024-11-08","arxiv_id":"2411.05547","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-cluster-resilience-llm-agent-based","title":"Enhancing Cluster Resilience: LLM-agent Based Autonomous Intelligent Cluster Diagnosis System and Evaluation Framework","date":"2024-11-08","arxiv_id":"2411.05349","repositories_listed":0,"syntology":null},{"url":null,"slug":"ev2r-evaluating-evidence-retrieval-in","title":"Ev2R: Evaluating Evidence Retrieval in Automated Fact-Checking","date":"2024-11-08","arxiv_id":"2411.05375","repositories_listed":0,"syntology":null},{"url":null,"slug":"gpt-semantic-cache-reducing-llm-costs-and","title":"GPT Semantic Cache: Reducing LLM Costs and Latency via Semantic Embedding Caching","date":"2024-11-08","arxiv_id":"2411.05276","repositories_listed":0,"syntology":null},{"url":null,"slug":"qwen2-5-32b-leveraging-self-consistent-tool","title":"Qwen2.5-32B: Leveraging Self-Consistent Tool-Integrated Reasoning for Bengali Mathematical Olympiad Problem Solving","date":"2024-11-08","arxiv_id":"2411.05934","repositories_listed":0,"syntology":null},{"url":null,"slug":"reducing-distraction-in-long-context-language","title":"Reducing Distraction in Long-Context Language Models by Focused Learning","date":"2024-11-08","arxiv_id":"2411.05928","repositories_listed":0,"syntology":null},{"url":null,"slug":"audiobox-tta-rag-improving-zero-shot-and-few","title":"Audiobox TTA-RAG: Improving Zero-Shot and Few-Shot Text-To-Audio with Retrieval-Augmented Generation","date":"2024-11-07","arxiv_id":"2411.05141","repositories_listed":0,"syntology":null},{"url":null,"slug":"dnn-based-3d-cloud-retrieval-for-variable","title":"DNN-based 3D Cloud Retrieval for Variable Solar Illumination and Multiview Spaceborne Imaging","date":"2024-11-07","arxiv_id":"2411.04682","repositories_listed":0,"syntology":null},{"url":null,"slug":"m3docrag-multi-modal-retrieval-is-what-you","title":"M3DocRAG: Multi-modal Retrieval is What You Need for Multi-page Multi-document Understanding","date":"2024-11-07","arxiv_id":"2411.04952","repositories_listed":0,"syntology":null},{"url":null,"slug":"needle-threading-can-llms-follow-threads","title":"Needle Threading: Can LLMs Follow Threads through Near-Million-Scale Haystacks?","date":"2024-11-07","arxiv_id":"2411.05000","repositories_listed":0,"syntology":null},{"url":null,"slug":"retrievegpt-merging-prompts-and-mathematical","title":"RetrieveGPT: Merging Prompts and Mathematical Models for Enhanced Code-Mixed Information Retrieval","date":"2024-11-07","arxiv_id":"2411.04752","repositories_listed":0,"syntology":null},{"url":null,"slug":"uncertainty-prediction-neural-network-upnet","title":"Uncertainty Prediction Neural Network (UpNet): Embedding Artificial Neural Network in Bayesian Inversion Framework to Quantify the Uncertainty of Remote Sensing Retrieval","date":"2024-11-07","arxiv_id":"2411.04556","repositories_listed":0,"syntology":null},{"url":null,"slug":"advanced-rag-models-with-graph-structures","title":"Advanced RAG Models with Graph Structures: Optimizing Complex Knowledge Reasoning and Text Generation","date":"2024-11-06","arxiv_id":"2411.03572","repositories_listed":0,"syntology":null},{"url":null,"slug":"fine-grained-guidance-for-retrievers","title":"Fine-Grained Guidance for Retrievers: Leveraging LLMs' Feedback in Retrieval-Augmented Generation","date":"2024-11-06","arxiv_id":"2411.03957","repositories_listed":0,"syntology":null},{"url":null,"slug":"lego-graphrag-modularizing-graph-based","title":"LEGO-GraphRAG: Modularizing Graph-based Retrieval-Augmented Generation for Design Space Exploration","date":"2024-11-06","arxiv_id":"2411.05844","repositories_listed":0,"syntology":null},{"url":null,"slug":"reproducible-hybrid-time-travel-retrieval-in","title":"Reproducible Hybrid Time-Travel Retrieval in Evolving Corpora","date":"2024-11-06","arxiv_id":"2411.04051","repositories_listed":0,"syntology":null},{"url":null,"slug":"select2plan-training-free-icl-based-planning","title":"Select2Plan: Training-Free ICL-Based Planning through VQA and Memory Retrieval","date":"2024-11-06","arxiv_id":"2411.04006","repositories_listed":0,"syntology":null},{"url":null,"slug":"cad-nerf-learning-nerfs-from-uncalibrated-few","title":"CAD-NeRF: Learning NeRFs from Uncalibrated Few-view Images by CAD Model Retrieval","date":"2024-11-05","arxiv_id":"2411.02979","repositories_listed":0,"syntology":null},{"url":null,"slug":"jpec-a-novel-graph-neural-network-for","title":"JPEC: A Novel Graph Neural Network for Competitor Retrieval in Financial Knowledge Graphs","date":"2024-11-05","arxiv_id":"2411.02692","repositories_listed":0,"syntology":null},{"url":null,"slug":"memory-augmented-cross-encoders-for","title":"Bridging Personalization and Control in Scientific Personalized Search","date":"2024-11-05","arxiv_id":"2411.02790","repositories_listed":0,"syntology":null},{"url":null,"slug":"persianrag-a-retrieval-augmented-generation","title":"PersianRAG: A Retrieval-Augmented Generation System for Persian Language","date":"2024-11-05","arxiv_id":"2411.02832","repositories_listed":0,"syntology":null},{"url":null,"slug":"washtsapp-a-rag-powered-whatsapp-chatbot-for","title":"WASHtsApp -- A RAG-powered WhatsApp Chatbot for supporting rural African clean water access, sanitation and hygiene","date":"2024-11-05","arxiv_id":"2411.02850","repositories_listed":0,"syntology":null},{"url":"/paper/exploring-optimal-transport-based-multi","slug":"exploring-optimal-transport-based-multi","title":"Exploring Optimal Transport-Based Multi-Grained Alignments for Text-Molecule Retrieval","date":"2024-11-04","arxiv_id":"2411.11875","repositories_listed":0,"syntology":null},{"url":null,"slug":"extracting-unlearned-information-from-llms","title":"Extracting Unlearned Information from LLMs with Activation Steering","date":"2024-11-04","arxiv_id":"2411.02631","repositories_listed":0,"syntology":null},{"url":null,"slug":"mm-embed-universal-multimodal-retrieval-with","title":"MM-Embed: Universal Multimodal Retrieval with Multimodal LLMs","date":"2024-11-04","arxiv_id":"2411.02571","repositories_listed":0,"syntology":null},{"url":null,"slug":"prompting-with-phonemes-enhancing-llm","title":"Prompting with Phonemes: Enhancing LLM Multilinguality for non-Latin Script Languages","date":"2024-11-04","arxiv_id":"2411.02398","repositories_listed":0,"syntology":null},{"url":null,"slug":"spectrum-semantic-processing-and-emotion","title":"SPECTRUM: Semantic Processing and Emotion-informed video-Captioning Through Retrieval and Understanding Modalities","date":"2024-11-04","arxiv_id":"2411.01975","repositories_listed":0,"syntology":null},{"url":null,"slug":"data-extraction-attacks-in-retrieval","title":"Data Extraction Attacks in Retrieval-Augmented Generation via Backdoors","date":"2024-11-03","arxiv_id":"2411.01705","repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-medical-image-retrieval-using","title":"Efficient Medical Image Retrieval Using DenseNet and FAISS for BIRADS Classification","date":"2024-11-03","arxiv_id":"2411.01473","repositories_listed":0,"syntology":null},{"url":null,"slug":"infant-agent-a-tool-integrated-logic-driven","title":"Infant Agent: A Tool-Integrated, Logic-Driven Agent with Cost-Effective API Usage","date":"2024-11-02","arxiv_id":"2411.01114","repositories_listed":0,"syntology":null},{"url":null,"slug":"lora-contextualizing-adaptation-of-large","title":"LoRA-Contextualizing Adaptation of Large Multimodal Models for Long Document Understanding","date":"2024-11-02","arxiv_id":"2411.01106","repositories_listed":0,"syntology":null},{"url":null,"slug":"corag-a-cost-constrained-retrieval","title":"CORAG: A Cost-Constrained Retrieval Optimization System for Retrieval-Augmented Generation","date":"2024-11-01","arxiv_id":"2411.00744","repositories_listed":0,"syntology":null},{"url":null,"slug":"e2e-afg-an-end-to-end-model-with-adaptive","title":"E2E-AFG: An End-to-End Model with Adaptive Filtering for Retrieval-Augmented Generation","date":"2024-11-01","arxiv_id":"2411.00437","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-question-answering-precision-with","title":"Enhancing Question Answering Precision with Optimized Vector Retrieval and Instructions","date":"2024-11-01","arxiv_id":"2411.01039","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-few-shot-cross-domain-named-entity","title":"Improving Few-Shot Cross-Domain Named Entity Recognition by Instruction Tuning a Word-Embedding based Retrieval Augmented Large Language Model","date":"2024-11-01","arxiv_id":"2411.00451","repositories_listed":0,"syntology":null},{"url":"/paper/infact-a-strong-baseline-for-automated-fact","slug":"infact-a-strong-baseline-for-automated-fact","title":"InFact: A Strong Baseline for Automated Fact-Checking","date":"2024-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"llm-ref-enhancing-reference-handling-in","title":"LLM-Ref: Enhancing Reference Handling in Technical Writing with Large Language Models","date":"2024-11-01","arxiv_id":"2411.00294","repositories_listed":0,"syntology":null},{"url":null,"slug":"optimizing-contextual-speech-recognition","title":"Optimizing Contextual Speech Recognition Using Vector Quantization for Efficient Retrieval","date":"2024-11-01","arxiv_id":"2411.00664","repositories_listed":0,"syntology":null},{"url":null,"slug":"provenance-a-light-weight-fact-checker-for","title":"Provenance: A Light-weight Fact-checker for Retrieval Augmented LLM Generation Output","date":"2024-11-01","arxiv_id":"2411.01022","repositories_listed":0,"syntology":null},{"url":null,"slug":"retrieval-enriched-zero-shot-image","title":"Retrieval-enriched zero-shot image classification in low-resource domains","date":"2024-11-01","arxiv_id":"2411.00988","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-multi-source-retrieval-augmented","title":"Towards Multi-Source Retrieval-Augmented Generation via Synergizing Reasoning and Preference-Driven Retrieval","date":"2024-11-01","arxiv_id":"2411.00689","repositories_listed":0,"syntology":null},{"url":null,"slug":"unified-generative-and-discriminative","title":"Unified Generative and Discriminative Training for Multi-modal Large Language Models","date":"2024-11-01","arxiv_id":"2411.00304","repositories_listed":0,"syntology":null},{"url":null,"slug":"judgerank-leveraging-large-language-models","title":"JudgeRank: Leveraging Large Language Models for Reasoning-Intensive Reranking","date":"2024-10-31","arxiv_id":"2411.00142","repositories_listed":0,"syntology":null},{"url":null,"slug":"leaf-learning-and-evaluation-augmented-by","title":"LEAF: Learning and Evaluation Augmented by Fact-Checking to Improve Factualness in Large Language Models","date":"2024-10-31","arxiv_id":"2410.23526","repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-large-language-models-for-medical","title":"Leveraging Large Language Models for Medical Information Extraction and Query Generation","date":"2024-10-31","arxiv_id":"2410.23851","repositories_listed":0,"syntology":null},{"url":null,"slug":"motadual-modality-task-dual-alignment-for","title":"MoTaDual: Modality-Task Dual Alignment for Enhanced Zero-shot Composed Image Retrieval","date":"2024-10-31","arxiv_id":"2410.23736","repositories_listed":0,"syntology":null},{"url":null,"slug":"responsible-retrieval-augmented-generation","title":"Responsible Retrieval Augmented Generation for Climate Decision Making from Documents","date":"2024-10-31","arxiv_id":"2410.23902","repositories_listed":0,"syntology":null},{"url":null,"slug":"eliciting-critical-reasoning-in-retrieval","title":"Eliciting Critical Reasoning in Retrieval-Augmented Language Models via Contrastive Explanations","date":"2024-10-30","arxiv_id":"2410.22874","repositories_listed":0,"syntology":null},{"url":null,"slug":"grounding-by-trying-llms-with-reinforcement","title":"Grounding by Trying: LLMs with Reinforcement Learning-Enhanced Retrieval","date":"2024-10-30","arxiv_id":"2410.23214","repositories_listed":0,"syntology":null},{"url":null,"slug":"hijackrag-hijacking-attacks-against-retrieval","title":"HijackRAG: Hijacking Attacks against Retrieval-Augmented Large Language Models","date":"2024-10-30","arxiv_id":"2410.22832","repositories_listed":0,"syntology":null},{"url":null,"slug":"mind-the-gap-a-generalized-approach-for-cross","title":"Mind the Gap: A Generalized Approach for Cross-Modal Embedding Alignment","date":"2024-10-30","arxiv_id":"2410.23437","repositories_listed":0,"syntology":null},{"url":null,"slug":"retrieval-augmented-generation-with","title":"Retrieval-Augmented Generation with Estimation of Source Reliability","date":"2024-10-30","arxiv_id":"2410.22954","repositories_listed":0,"syntology":null},{"url":null,"slug":"textsc-long-2-rag-evaluating-long-context","title":"Long$^2$RAG: Evaluating Long-Context & Long-Form Retrieval-Augmented Generation with Key Point Recall","date":"2024-10-30","arxiv_id":"2410.23000","repositories_listed":0,"syntology":null},{"url":null,"slug":"application-of-audio-fingerprinting","title":"Application of Audio Fingerprinting Techniques for Real-Time Scalable Speech Retrieval and Speech Clusterization","date":"2024-10-29","arxiv_id":"2410.21876","repositories_listed":0,"syntology":null},{"url":null,"slug":"realcqa-v2-visual-premise-proving","title":"RealCQA-V2 : Visual Premise Proving A Manual COT Dataset for Charts","date":"2024-10-29","arxiv_id":"2410.22492","repositories_listed":0,"syntology":null},{"url":null,"slug":"retrieval-augmented-approach-for-unsupervised","title":"Retrieval-Augmented Approach for Unsupervised Anomalous Sound Detection and Captioning without Model Training","date":"2024-10-29","arxiv_id":"2410.22056","repositories_listed":0,"syntology":null},{"url":null,"slug":"understanding-synthetic-context-extension-via","title":"Understanding Synthetic Context Extension via Retrieval Heads","date":"2024-10-29","arxiv_id":"2410.22316","repositories_listed":0,"syntology":null},{"url":null,"slug":"calibrated-decision-making-through-llm","title":"Calibrated Decision-Making through LLM-Assisted Retrieval","date":"2024-10-28","arxiv_id":"2411.08891","repositories_listed":0,"syntology":null},{"url":null,"slug":"fact-examining-the-effectiveness-of-iterative","title":"FACT: Examining the Effectiveness of Iterative Context Rewriting for Multi-fact Retrieval","date":"2024-10-28","arxiv_id":"2410.21012","repositories_listed":0,"syntology":null},{"url":null,"slug":"plan-times-rag-planning-guided-retrieval","title":"Plan$\\times$RAG: Planning-guided Retrieval Augmented Generation","date":"2024-10-28","arxiv_id":"2410.20753","repositories_listed":0,"syntology":null},{"url":null,"slug":"sandboxaq-s-submission-to-mrl-2024-shared","title":"SandboxAQ's submission to MRL 2024 Shared Task on Multi-lingual Multi-task Information Retrieval","date":"2024-10-28","arxiv_id":"2410.21501","repositories_listed":0,"syntology":null},{"url":null,"slug":"zero-shot-dense-retrieval-with-embeddings","title":"Zero-Shot Dense Retrieval with Embeddings from Relevance Feedback","date":"2024-10-28","arxiv_id":"2410.21242","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-based-dense-retrieval-a","title":"Deep Learning Based Dense Retrieval: A Comparative Study","date":"2024-10-27","arxiv_id":"2410.20315","repositories_listed":0,"syntology":null},{"url":null,"slug":"r-3ag-first-workshop-on-refined-and-reliable","title":"R^3AG: First Workshop on Refined and Reliable Retrieval Augmented Generation","date":"2024-10-27","arxiv_id":"2410.20598","repositories_listed":0,"syntology":null},{"url":null,"slug":"what-factors-affect-multi-modal-in-context","title":"What Factors Affect Multi-Modal In-Context Learning? An In-Depth Exploration","date":"2024-10-27","arxiv_id":"2410.20482","repositories_listed":0,"syntology":null},{"url":null,"slug":"windtunnel-a-framework-for-community-aware","title":"WindTunnel -- A Framework for Community Aware Sampling of Large Corpora","date":"2024-10-27","arxiv_id":"2410.20301","repositories_listed":0,"syntology":null},{"url":null,"slug":"give-guiding-visual-encoder-to-perceive","title":"GiVE: Guiding Visual Encoder to Perceive Overlooked Information","date":"2024-10-26","arxiv_id":"2410.20109","repositories_listed":0,"syntology":null},{"url":null,"slug":"kisanqrs-a-deep-learning-based-automated","title":"KisanQRS: A Deep Learning-based Automated Query-Response System for Agricultural Decision-Making","date":"2024-10-26","arxiv_id":"2411.08883","repositories_listed":0,"syntology":null},{"url":null,"slug":"mad-sherlock-multi-agent-debates-for-out-of","title":"LLM-Consensus: Multi-Agent Debate for Visual Misinformation Detection","date":"2024-10-26","arxiv_id":"2410.20140","repositories_listed":0,"syntology":null},{"url":null,"slug":"mask-based-membership-inference-attacks-for","title":"Mask-based Membership Inference Attacks for Retrieval-Augmented Generation","date":"2024-10-26","arxiv_id":"2410.20142","repositories_listed":0,"syntology":null},{"url":null,"slug":"matexpert-decomposing-materials-discovery-by","title":"MatExpert: Decomposing Materials Discovery by Mimicking Human Experts","date":"2024-10-26","arxiv_id":"2410.21317","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-field-adaptive-retrieval","title":"Multi-Field Adaptive Retrieval","date":"2024-10-26","arxiv_id":"2410.20056","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-path-exploration-and-feedback","title":"Multi-path Exploration and Feedback Adjustment for Text-to-Image Person Retrieval","date":"2024-10-26","arxiv_id":"2410.21318","repositories_listed":0,"syntology":null},{"url":null,"slug":"agent-cq-automatic-generation-and-evaluation","title":"AGENT-CQ: Automatic Generation and Evaluation of Clarifying Questions for Conversational Search with LLMs","date":"2024-10-25","arxiv_id":"2410.19692","repositories_listed":0,"syntology":null},{"url":null,"slug":"chunkrag-novel-llm-chunk-filtering-method-for","title":"ChunkRAG: Novel LLM-Chunk Filtering Method for RAG Systems","date":"2024-10-25","arxiv_id":"2410.19572","repositories_listed":0,"syntology":null},{"url":null,"slug":"pebr-a-probabilistic-approach-to-embedding","title":"pEBR: A Probabilistic Approach to Embedding Based Retrieval","date":"2024-10-25","arxiv_id":"2410.19349","repositories_listed":0,"syntology":null},{"url":null,"slug":"taxonomy-guided-semantic-indexing-for","title":"Taxonomy-guided Semantic Indexing for Academic Paper Search","date":"2024-10-25","arxiv_id":"2410.19218","repositories_listed":0,"syntology":null},{"url":null,"slug":"aggregated-knowledge-model-enhancing-domain","title":"Aggregated Knowledge Model: Enhancing Domain-Specific QA with Fine-Tuned and Retrieval-Augmented Generation Models","date":"2024-10-24","arxiv_id":"2410.18344","repositories_listed":0,"syntology":null},{"url":null,"slug":"geometric-feature-enhanced-knowledge-graph","title":"Geometric Feature Enhanced Knowledge Graph Embedding and Spatial Reasoning","date":"2024-10-24","arxiv_id":"2410.18345","repositories_listed":0,"syntology":null},{"url":null,"slug":"probing-ranking-llms-mechanistic","title":"Understanding Ranking LLMs: A Mechanistic Analysis for Information Retrieval","date":"2024-10-24","arxiv_id":"2410.18527","repositories_listed":0,"syntology":null},{"url":null,"slug":"retrieving-implicit-and-explicit-emotional","title":"Retrieving Implicit and Explicit Emotional Events Using Large Language Models","date":"2024-10-24","arxiv_id":"2410.19128","repositories_listed":0,"syntology":null},{"url":null,"slug":"simrag-self-improving-retrieval-augmented","title":"SimRAG: Self-Improving Retrieval-Augmented Generation for Adapting Large Language Models to Specialized Domains","date":"2024-10-23","arxiv_id":"2410.17952","repositories_listed":0,"syntology":null},{"url":null,"slug":"atomic-fact-decomposition-helps-attributed","title":"Atomic Fact Decomposition Helps Attributed Question Answering","date":"2024-10-22","arxiv_id":"2410.16708","repositories_listed":0,"syntology":null},{"url":null,"slug":"beyond-retrieval-generating-narratives-in","title":"Beyond Retrieval: Generating Narratives in Conversational Recommender Systems","date":"2024-10-22","arxiv_id":"2410.16780","repositories_listed":0,"syntology":null},{"url":null,"slug":"bridging-search-and-recommendation-in","title":"Bridging Search and Recommendation in Generative Retrieval: Does One Task Help the Other?","date":"2024-10-22","arxiv_id":"2410.16823","repositories_listed":0,"syntology":null},{"url":null,"slug":"denoise-i2w-mapping-images-to-denoising-words","title":"Denoise-I2W: Mapping Images to Denoising Words for Accurate Zero-Shot Composed Image Retrieval","date":"2024-10-22","arxiv_id":"2410.17393","repositories_listed":0,"syntology":null},{"url":null,"slug":"distill-synthkg-distilling-knowledge-graph","title":"Distill-SynthKG: Distilling Knowledge Graph Synthesis Workflow for Improved Coverage and Efficiency","date":"2024-10-22","arxiv_id":"2410.16597","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-answer-attribution-for-faithful","title":"Enhancing Answer Attribution for Faithful Text Generation with Large Language Models","date":"2024-10-22","arxiv_id":"2410.17112","repositories_listed":0,"syntology":null},{"url":null,"slug":"ptychoformer-a-transformer-based-model-for","title":"PtychoFormer: A Transformer-based Model for Ptychographic Phase Retrieval","date":"2024-10-22","arxiv_id":"2410.17377","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-survey-of-conversational-search","title":"A Survey of Conversational Search","date":"2024-10-21","arxiv_id":"2410.15576","repositories_listed":0,"syntology":null}],"record_sha256":"7428907ed737e24f15f70b580cb94e458cf41d446a3aa0b2bec07a1f336dceb6","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}