{"total":81,"rows":[{"id":"2406.00515","title":"A Survey on Large Language Models for Code Generation","created":"2024-06-01","cited_by_count":658,"area":null},{"id":"2405.07437","title":"Evaluation of Retrieval-Augmented Generation: A Survey","created":"2024-05-13","cited_by_count":146,"area":"rag"},{"id":"2406.13629","title":"InstructRAG: Instructing Retrieval-Augmented Generation via Self-Synthesized Rationales","created":"2024-06-19","cited_by_count":101,"area":"rag"},{"id":"2403.03187","title":"Reliable, Adaptable, and Attributable Language Models with Retrieval","created":"2024-03-05","cited_by_count":73,"area":"rag"},{"id":"2402.11260","title":"MoRAL: MoE Augmented LoRA for LLMs' Lifelong Learning","created":"2024-02-17","cited_by_count":63,"area":"moe"},{"id":"2403.01432","title":"Fine Tuning vs. Retrieval Augmented Generation for Less Popular Knowledge","created":"2024-03-03","cited_by_count":50,"area":"rag"},{"id":"2403.16073","title":"Combining Fine-Tuning and LLM-based Agents for Intuitive Smart Contract Auditing with Justifications","created":"2024-03-24","cited_by_count":41,"area":"agents"},{"id":"2404.15939","title":"Telco-RAG: Navigating the Challenges of Retrieval-Augmented Language Models for Telecommunications","created":"2024-04-24","cited_by_count":26,"area":"rag"},{"id":"2402.12869","title":"Exploring the Impact of Table-to-Text Methods on Augmenting LLM-based Question Answering with Domain Hybrid Data","created":"2024-02-20","cited_by_count":24,"area":null},{"id":"2412.14964","title":"Efficient Knowledge Injection in LLMs via Self-Distillation","created":"2024-12-19","cited_by_count":24,"area":"distill"},{"id":"2402.07483","title":"T-RAG: Lessons from the LLM Trenches","created":"2024-02-12","cited_by_count":23,"area":null},{"id":"2405.13003","title":"A Survey on Recent Advances in Conversational Data Generation","created":"2024-05-12","cited_by_count":23,"area":null},{"id":"2412.15235","title":"OG-RAG: Ontology-Grounded Retrieval-Augmented Generation For Large Language Models","created":"2024-12-12","cited_by_count":23,"area":"rag"},{"id":"2402.07179","title":"Prompt Perturbation in Retrieval-Augmented Generation based Large Language Models","created":"2024-02-11","cited_by_count":18,"area":"rag"},{"id":"2412.10543","title":"METIS: Fast Quality-Aware RAG Systems with Configuration Adaptation","created":"2024-12-13","cited_by_count":17,"area":"rag"},{"id":"2405.03085","title":"Compressing Long Context for Enhancing RAG with AMR-based Concept Distillation","created":"2024-05-06","cited_by_count":16,"area":"rag"},{"id":"2409.13761","title":"Do Large Language Models Need a Content Delivery Network?","created":"2024-09-16","cited_by_count":16,"area":"inference"},{"id":"2504.10568","title":"AgMMU: A Comprehensive Agricultural Multimodal Understanding Benchmark","created":"2025-04-14","cited_by_count":16,"area":"mllm"},{"id":"2410.22349","title":"Search Engines in an AI Era: The False Promise of Factual and Verifiable Source-Cited Responses","created":"2024-10-15","cited_by_count":15,"area":null},{"id":"2502.04176","title":"MRAMG-Bench: A Comprehensive Benchmark for Advancing Multimodal Retrieval-Augmented Multimodal Generation","created":"2025-02-06","cited_by_count":15,"area":"rag"},{"id":"2407.01972","title":"MeMemo: On-device Retrieval Augmentation for Private and Personalized Text Generation","created":"2024-07-02","cited_by_count":13,"area":"rag"},{"id":"2502.18635","title":"Faster, Cheaper, Better: Multi-Objective Hyperparameter Optimization for LLM and RAG Systems","created":"2025-02-25","cited_by_count":12,"area":"rag"},{"id":"2509.04499","title":"DeepTRACE: Auditing Deep Research AI Systems for Tracking Reliability Across Citations and Evidence","created":"2025-09-02","cited_by_count":10,"area":"agents"},{"id":"2409.13537","title":"ShizishanGPT: An Agricultural Large Language Model Integrating Tools and Resources","created":"2024-09-20","cited_by_count":9,"area":null},{"id":"2403.07805","title":"Beyond Memorization: The Challenge of Random Memory Access in Language Models","created":"2024-03-12","cited_by_count":8,"area":null},{"id":"2407.19994","title":"A Study on the Implementation Method of an Agent-Based Advanced RAG System Using Graph","created":"2024-07-29","cited_by_count":8,"area":"rag"},{"id":"2410.08821","title":"DeepNote: Note-Centric Deep Retrieval-Augmented Generation","created":"2024-10-11","cited_by_count":8,"area":"rag"},{"id":"2504.07724","title":"The Multi-Round Diagnostic RAG Framework for Emulating Clinical Reasoning","created":"2025-04-10","cited_by_count":8,"area":"lr"},{"id":"2407.20906","title":"Automated Review Generation Method Based on Large Language Models","created":"2024-07-30","cited_by_count":7,"area":null},{"id":"2409.19019","title":"RAGProbe: An Automated Approach for Evaluating RAG Applications","created":"2024-09-24","cited_by_count":7,"area":"rag"},{"id":"2410.15805","title":"RAG4ITOps: A Supervised Fine-Tunable and Comprehensive RAG Framework for IT Operations and Maintenance","created":"2024-10-21","cited_by_count":7,"area":"rag"},{"id":"2502.12477","title":"Savaal: Scalable Concept-Driven Question Generation to Enhance Human Learning","created":"2025-02-18","cited_by_count":7,"area":null},{"id":"2404.17401","title":"Evaluation of Geographical Distortions in Language Models","created":"2024-04-26","cited_by_count":6,"area":null},{"id":"2408.09017","title":"Meta Knowledge for Retrieval Augmented Large Language Models","created":"2024-08-16","cited_by_count":6,"area":"rag"},{"id":"2409.03274","title":"Recent Advances in Attack and Defense Approaches of Large Language Models","created":"2024-09-05","cited_by_count":6,"area":null},{"id":"2506.15690","title":"LLM Web Dynamics: Tracing Model Collapse in a Network of LLMs","created":"2025-05-26","cited_by_count":6,"area":"synth"},{"id":"2508.17094","title":"PowerChain: A Verifiable Agentic AI System for Automating Distribution Grid Analyses","created":"2025-08-23","cited_by_count":6,"area":"agents"},{"id":"2405.20347","title":"Small Language Models for Application Interactions: A Case Study","created":"2024-05-23","cited_by_count":5,"area":null},{"id":"2407.04528","title":"GPT vs RETRO: Exploring the Intersection of Retrieval and Parameter-Efficient Fine-Tuning","created":"2024-07-05","cited_by_count":5,"area":"rag"},{"id":"2408.02545","title":"RAG Foundry: A Framework for Enhancing LLMs for Retrieval Augmented Generation","created":"2024-08-05","cited_by_count":5,"area":"rag"},{"id":"2504.14858","title":"Retrieval is Not Enough: Enhancing RAG Reasoning through Test-Time Critique and Optimization","created":"2025-04-21","cited_by_count":5,"area":"lr"},{"id":"2401.10733","title":"Dynamic Q&A of Clinical Documents with Large Language Models","created":"2024-01-19","cited_by_count":4,"area":null},{"id":"2505.13129","title":"Optimizing Retrieval Augmented Generation for Object Constraint Language","created":"2025-05-19","cited_by_count":4,"area":"rag"},{"id":"2512.10114","title":"AgriRegion: Region-Aware Retrieval for High-Fidelity Agricultural Advice","created":"2025-12-10","cited_by_count":4,"area":"rag"},{"id":"2406.03963","title":"A + B: A General Generator-Reader Framework for Optimizing LLMs to Unleash Synergy Potential","created":"2024-06-06","cited_by_count":3,"area":"rag"},{"id":"2409.20434","title":"QAEncoder: Towards Aligned Representation Learning in Question Answering Systems","created":"2024-09-30","cited_by_count":3,"area":"rag"},{"id":"2410.09629","title":"Synthetic Knowledge Ingestion: Towards Knowledge Refinement and Injection for Enhancing Large Language Models","created":"2024-10-12","cited_by_count":3,"area":null},{"id":"2506.13023","title":"A Practical Guide for Evaluating LLMs and LLM-Reliant Systems","created":"2025-06-16","cited_by_count":3,"area":null},{"id":"2509.14608","title":"Enterprise AI Must Enforce Participant-Aware Access Control","created":"2025-09-18","cited_by_count":3,"area":null},{"id":"2601.06352","title":"CARD: Cluster-level Adaptation with Reward-guided Decoding for Personalized Text Generation","created":"2026-01-09","cited_by_count":3,"area":"alignment"},{"id":"2402.12177","title":"Mafin: Enhancing Black-Box Embeddings with Model Augmented Fine-Tuning","created":"2024-02-19","cited_by_count":2,"area":"rag"},{"id":"2411.15203","title":"Multimodal large language model for wheat breeding: a new exploration of smart breeding","created":"2024-11-20","cited_by_count":2,"area":"mllm"},{"id":"2505.01307","title":"Document Retrieval Augmented Fine-Tuning (DRAFT) for safety-critical software assessments","created":"2025-05-02","cited_by_count":2,"area":"rag"},{"id":"2505.08905","title":"Grounding Synthetic Data Evaluations of Language Models in Unsupervised Document Corpora","created":"2025-05-13","cited_by_count":2,"area":"synth"},{"id":"2507.01259","title":"GAIus: Combining Genai with Legal Clauses Retrieval for Knowledge-based Assistant","created":"2025-07-02","cited_by_count":2,"area":null},{"id":"2508.06178","title":"Comparing Knowledge Injection Methods for LLMs in a Low-Resource Regime","created":"2025-08-08","cited_by_count":2,"area":null},{"id":"2509.14435","title":"Causal-Counterfactual RAG: The Integration of Causal-Counterfactual Reasoning into RAG","created":"2025-09-17","cited_by_count":2,"area":"lr"},{"id":"2509.23767","title":"From Personal to Collective: On the Role of Local and Global Memory in LLM Personalization","created":"2025-09-28","cited_by_count":2,"area":null},{"id":"2407.12822","title":"Lightweight Large Language Model for Medication Enquiry: Med-Pal","created":"2024-07-02","cited_by_count":1,"area":null},{"id":"2408.05911","title":"A New Pipeline For Generating Instruction Dataset via RAG and Self Fine-Tuning","created":"2024-08-12","cited_by_count":1,"area":null},{"id":"2411.05054","title":"FMEA Builder: Expert Guided Text Generation for Equipment Maintenance","created":"2024-11-07","cited_by_count":1,"area":null},{"id":"2412.14771","title":"ALKAFI-LLAMA3: Fine-Tuning LLMs for Precise Legal Understanding in Palestine","created":"2024-12-19","cited_by_count":1,"area":null},{"id":"2503.01131","title":"Beyond QA Pairs: Assessing Parameter-Efficient Fine-Tuning for Fact Embedding in LLMs","created":"2025-03-03","cited_by_count":1,"area":null},{"id":"2507.16974","title":"Leveraging Synthetic Data for Question Answering with Multilingual LLMs in the Agricultural Domain","created":"2025-07-22","cited_by_count":1,"area":"synth"},{"id":"2508.12682","title":"GridCodex: A RAG-Driven AI Framework for Power Grid Code Reasoning and Compliance","created":"2025-08-18","cited_by_count":1,"area":"lr"},{"id":"2604.18509","title":"MASS-RAG: Multi-Agent Synthesis Retrieval-Augmented Generation","created":"2026-04-20","cited_by_count":1,"area":"rag"},{"id":"2407.18044","title":"The Geometry of Queries: Query-Based Innovations in Retrieval-Augmented Generation for Healthcare QA","created":"2024-07-25","cited_by_count":0,"area":"rag"},{"id":"2411.19539","title":"Knowledge Management for Automobile Failure Analysis Using Graph RAG","created":"2024-11-29","cited_by_count":0,"area":"rag"},{"id":"2412.12961","title":"Adaptations of AI models for querying the LandMatrix database in natural language","created":"2024-12-17","cited_by_count":0,"area":null},{"id":"2506.06208","title":"Building Models of Neurological Language","created":"2025-06-06","cited_by_count":0,"area":null},{"id":"2506.18027","title":"PDF Retrieval Augmented Question Answering","created":"2025-06-22","cited_by_count":0,"area":"rag"},{"id":"2506.22852","title":"Knowledge Augmented Finetuning Matters in both RAG and Agent Based Dialog Systems","created":"2025-06-28","cited_by_count":0,"area":"agents"},{"id":"2511.05915","title":"CoEdge-RAG: Optimizing Hierarchical Scheduling for Retrieval-Augmented LLMs in Collaborative Edge Computing","created":"2025-11-08","cited_by_count":0,"area":"rag"},{"id":"2601.06362","title":"Do Implicit Personalization and Explicit Styles Conflict? PsPLUG: A Lightweight Plug-in for Balancing Personalization and Style in Customized LLMs","created":"2026-01-10","cited_by_count":0,"area":null},{"id":"2602.00030","title":"RAPTOR-AI for Disaster OODA Loop: Hierarchical Multimodal RAG with Experience-Driven Agentic Decision-Making","created":"2026-01-18","cited_by_count":0,"area":"agents"},{"id":"2603.13275","title":"PREBA: Surgical Duration Prediction via PCA-Weighted Retrieval-Augmented LLMs and Bayesian Averaging Aggregation","created":"2026-02-27","cited_by_count":0,"area":"rag"},{"id":"2605.23193","title":"CultivAgents: Cultivating Relationship-Centered Multi-Agent Systems for Personalized Gardening","created":"2026-05-22","cited_by_count":0,"area":null},{"id":"2606.26857","title":"LCAi: Life Cycle Assessment with big data fusion and retrieval-augmented generation-assisted interpretation","created":"2026-06-25","cited_by_count":0,"area":null},{"id":"2608.17616","title":"MoNe: Modular Neural Memory for Efficient Long Context Inference","created":"2026-08-18","cited_by_count":0,"area":null},{"id":"2610.01936","title":"Mapping the RAG Landscape: A Four Axis Taxonomy of Efficiency, Defense, Interactivity, and Reasoning","created":"2026-10-01","cited_by_count":0,"area":"lr"},{"id":"2610.02542","title":"How To Train Your World Model: Fine-tuning vs RAG for LM-based World Modeling","created":"2026-10-01","cited_by_count":0,"area":"wm"}],"next_cursor":null}