{"total":26,"rows":[{"id":"2307.06435","title":"A Comprehensive Overview of Large Language Models","created":"2023-07-12","cited_by_count":648,"area":null},{"id":"2310.10501","title":"NeMo Guardrails: A Toolkit for Controllable and Safe LLM Applications with Programmable Rails","created":"2023-10-16","cited_by_count":365,"area":null},{"id":"2310.03025","title":"Retrieval meets Long Context Large Language Models","created":"2023-10-04","cited_by_count":115,"area":null},{"id":"2311.07914","title":"Can Knowledge Graphs Reduce Hallucinations in LLMs? : A Survey","created":"2023-11-14","cited_by_count":92,"area":null},{"id":"2402.02420","title":"Factuality of Large Language Models: A Survey","created":"2024-02-04","cited_by_count":66,"area":null},{"id":"2407.12854","title":"Scaling Retrieval-Based Language Models with a Trillion-Token Datastore","created":"2024-07-09","cited_by_count":56,"area":null},{"id":"2402.12847","title":"Instruction-tuned Language Models are Better Knowledge Learners","created":"2024-02-20","cited_by_count":55,"area":null},{"id":"2305.13246","title":"Interactive Natural Language Processing","created":"2023-05-22","cited_by_count":31,"area":null},{"id":"2307.09751","title":"Information Retrieval Meets Large Language Models: A Strategic Report from Chinese IR Community","created":"2023-07-19","cited_by_count":29,"area":null},{"id":"2310.11761","title":"A Comprehensive Evaluation of Large Language Models on Legal Judgment Prediction","created":"2023-10-18","cited_by_count":28,"area":null},{"id":"2404.06001","title":"Privacy Preserving Prompt Engineering: A Survey","created":"2024-04-09","cited_by_count":25,"area":null},{"id":"2403.00815","title":"RAM-EHR: Retrieval Augmentation Meets Clinical Predictions on Electronic Health Records","created":"2024-02-25","cited_by_count":21,"area":null},{"id":"2407.09726","title":"On Mitigating Code LLM Hallucinations with API Documentation","created":"2024-07-13","cited_by_count":21,"area":null},{"id":"2307.02185","title":"Citation: A Key to Building Responsible and Accountable Large Language Models","created":"2023-07-05","cited_by_count":20,"area":null},{"id":"2307.01189","title":"Trainable Transformer in Transformer","created":"2023-07-03","cited_by_count":17,"area":null},{"id":"2402.11324","title":"EVEDIT: Event-based Knowledge Editing with Deductive Editing Boundaries","created":"2024-02-17","cited_by_count":16,"area":null},{"id":"2504.03101","title":"Single-Pass Document Scanning for Question Answering","created":"2025-04-04","cited_by_count":6,"area":null},{"id":"2602.00398","title":"MemoryLLM: Plug-n-Play Interpretable Feed-Forward Memory for Transformers","created":"2026-01-30","cited_by_count":5,"area":null},{"id":"2408.15491","title":"Enhancing and Accelerating Large Language Models via Instruction-Aware Contextual Compression","created":"2024-08-28","cited_by_count":4,"area":null},{"id":"2406.14473","title":"Data-Centric AI in the Age of Large Language Models","created":"2024-06-20","cited_by_count":2,"area":null},{"id":"2512.20245","title":"Memory as Resonance: A Biomimetic Architecture for Infinite Context Memory on Ergodic Phonetic Manifolds","created":"2025-12-23","cited_by_count":1,"area":null},{"id":"2507.08214","title":"Depth-Sequence Transformer (DST) for Segment-Specific ICA Calcification Mapping on Non-Contrast CT","created":"2025-07-10","cited_by_count":0,"area":null},{"id":"2509.23417","title":"Retrieval-Constrained Decoding Reveals Underestimated Parametric Knowledge in Language Models","created":"2025-09-27","cited_by_count":0,"area":null},{"id":"2512.06048","title":"The Road of Adaptive AI for Precision in Cybersecurity","created":"2025-12-05","cited_by_count":0,"area":null},{"id":"2605.06216","title":"TIDE: Every Layer Knows the Token Beneath the Context","created":"2026-05-07","cited_by_count":0,"area":null},{"id":"2605.11447","title":"Conditional Memory Enhanced Item Representation for Generative Recommendation","created":"2026-05-12","cited_by_count":0,"area":null}],"next_cursor":null}