{"total":73,"rows":[{"id":"2407.02485","title":"RankRAG: Unifying Context Ranking with Retrieval-Augmented Generation in LLMs","created":"2024-07-02","cited_by_count":202,"area":"rag"},{"id":"2407.12883","title":"BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval","created":"2024-07-16","cited_by_count":158,"area":null},{"id":"2410.02694","title":"HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly","created":"2024-10-03","cited_by_count":125,"area":null},{"id":"2406.13629","title":"InstructRAG: Instructing Retrieval-Augmented Generation via Self-Synthesized Rationales","created":"2024-06-19","cited_by_count":101,"area":"rag"},{"id":"2406.14497","title":"CodeRAG-Bench: Can Retrieval Augment Code Generation?","created":"2024-06-20","cited_by_count":91,"area":"rag"},{"id":"2411.06037","title":"Sufficient Context: A New Lens on Retrieval Augmented Generation Systems","created":"2024-11-09","cited_by_count":72,"area":"rag"},{"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":"2407.21439","title":"MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Reranking and Noise-injected Training","created":"2024-07-31","cited_by_count":50,"area":"mllm"},{"id":"2406.12934","title":"Current state of LLM Risks and AI Guardrails","created":"2024-06-16","cited_by_count":46,"area":"safety"},{"id":"2404.03302","title":"How Easily do Irrelevant Inputs Skew the Responses of Large Language Models?","created":"2024-04-04","cited_by_count":44,"area":null},{"id":"2408.01262","title":"RAGEval: Scenario Specific RAG Evaluation Dataset Generation Framework","created":"2024-08-02","cited_by_count":39,"area":"rag"},{"id":"2404.06347","title":"RAR-b: Reasoning as Retrieval Benchmark","created":"2024-04-09","cited_by_count":36,"area":"lr"},{"id":"2404.15127","title":"GSCo: Towards Generalizable AI in Medicine via Generalist-Specialist Collaboration","created":"2024-04-23","cited_by_count":34,"area":null},{"id":"2411.12644","title":"CodeXEmbed: A Generalist Embedding Model Family for Multiligual and Multi-task Code Retrieval","created":"2024-11-19","cited_by_count":34,"area":null},{"id":"2410.13509","title":"RAG-DDR: Optimizing Retrieval-Augmented Generation Using Differentiable Data Rewards","created":"2024-10-17","cited_by_count":33,"area":"rag"},{"id":"2407.01102","title":"BERGEN: A Benchmarking Library for Retrieval-Augmented Generation","created":"2024-07-01","cited_by_count":31,"area":"rag"},{"id":"2412.14457","title":"VISA: Retrieval Augmented Generation with Visual Source Attribution","created":"2024-12-19","cited_by_count":28,"area":"rag"},{"id":"2505.18405","title":"RaDeR: Reasoning-aware Dense Retrieval Models","created":"2025-05-23","cited_by_count":27,"area":"lr"},{"id":"2407.09252","title":"Context Embeddings for Efficient Answer Generation in RAG","created":"2024-07-12","cited_by_count":26,"area":"rag"},{"id":"2405.19325","title":"Nearest Neighbor Speculative Decoding for LLM Generation and Attribution","created":"2024-05-29","cited_by_count":25,"area":"inference"},{"id":"2410.14675","title":"To Trust or Not to Trust? Enhancing Large Language Models' Situated Faithfulness to External Contexts","created":"2024-10-18","cited_by_count":25,"area":"rag"},{"id":"2501.00353","title":"RAG-Instruct: Boosting LLMs with Diverse Retrieval-Augmented Instructions","created":"2024-12-31","cited_by_count":25,"area":"rag"},{"id":"2501.16214","title":"Provence: efficient and robust context pruning for retrieval-augmented generation","created":"2025-01-27","cited_by_count":25,"area":"rag"},{"id":"2502.17832","title":"MM-PoisonRAG: Disrupting Multimodal RAG with Local and Global Poisoning Attacks","created":"2025-02-25","cited_by_count":24,"area":"mllm"},{"id":"2504.18041","title":"RAG LLMs are Not Safer: A Safety Analysis of Retrieval-Augmented Generation for Large Language Models","created":"2025-04-25","cited_by_count":24,"area":"rag"},{"id":"2412.13746","title":"RAG-RewardBench: Benchmarking Reward Models in Retrieval Augmented Generation for Preference Alignment","created":"2024-12-18","cited_by_count":23,"area":"rag"},{"id":"2510.16724","title":"A Comprehensive Survey on Reinforcement Learning-based Agentic Search: Foundations, Roles, Optimizations, Evaluations, and Applications","created":"2025-10-19","cited_by_count":22,"area":"rag"},{"id":"2404.12447","title":"AmbigDocs: Reasoning across Documents on Different Entities under the Same Name","created":"2024-04-18","cited_by_count":21,"area":null},{"id":"2501.01303","title":"Citations and Trust in LLM Generated Responses","created":"2025-01-02","cited_by_count":18,"area":null},{"id":"2404.03862","title":"Verifiable by Design: Aligning Language Models to Quote from Pre-Training Data","created":"2024-04-05","cited_by_count":13,"area":"alignment"},{"id":"2506.04202","title":"TracLLM: A Generic Framework for Attributing Long Context LLMs","created":"2025-06-04","cited_by_count":13,"area":null},{"id":"2502.17297","title":"Benchmarking Retrieval-Augmented Generation in Multi-Modal Contexts","created":"2025-02-24","cited_by_count":12,"area":"mllm"},{"id":"2502.00977","title":"Context-Aware Hierarchical Merging for Long Document Summarization","created":"2025-02-03","cited_by_count":9,"area":null},{"id":"2502.20969","title":"TeleRAG: Efficient Retrieval-Augmented Generation Inference with Lookahead Retrieval","created":"2025-02-28","cited_by_count":9,"area":"rag"},{"id":"2506.20051","title":"Controlled Retrieval-augmented Context Evaluation for Long-form RAG","created":"2025-06-24","cited_by_count":9,"area":"rag"},{"id":"2408.11815","title":"Great Memory, Shallow Reasoning: Limits of $k$NN-LMs","created":"2024-08-21","cited_by_count":8,"area":"lr"},{"id":"2412.10960","title":"Can LLMs Help Create Grammar?: Automating Grammar Creation for Endangered Languages with In-Context Learning","created":"2024-12-14","cited_by_count":8,"area":null},{"id":"2502.18817","title":"Judge as A Judge: Improving the Evaluation of Retrieval-Augmented Generation through the Judge-Consistency of Large Language Models","created":"2025-02-26","cited_by_count":8,"area":"rag"},{"id":"2510.23730","title":"Evaluating Long-Term Memory for Long-Context Question Answering","created":"2025-10-27","cited_by_count":8,"area":null},{"id":"2410.15801","title":"Improve Dense Passage Retrieval with Entailment Tuning","created":"2024-10-21","cited_by_count":7,"area":"rag"},{"id":"2508.03793","title":"AttnTrace: Contextual Attribution of Prompt Injection and Knowledge Corruption","created":"2025-08-05","cited_by_count":7,"area":"rag"},{"id":"2502.17888","title":"RankCoT: Refining Knowledge for Retrieval-Augmented Generation through Ranking Chain-of-Thoughts","created":"2025-02-25","cited_by_count":6,"area":"lr"},{"id":"2410.15667","title":"RAC: Efficient LLM Factuality Correction with Retrieval Augmentation","created":"2024-10-21","cited_by_count":5,"area":"rag"},{"id":"2405.15984","title":"Evaluating and Safeguarding the Adversarial Robustness of Retrieval-Based In-Context Learning","created":"2024-05-24","cited_by_count":4,"area":"rag"},{"id":"2410.18251","title":"Context-Augmented Code Generation Using Programming Knowledge Graphs","created":"2024-10-09","cited_by_count":4,"area":null},{"id":"2506.07309","title":"ConfRAG: Confidence-Guided Retrieval-Augmenting Generation","created":"2025-06-08","cited_by_count":4,"area":"rag"},{"id":"2410.03726","title":"Neurosymbolic AI approach to Attribution in Large Language Models","created":"2024-09-30","cited_by_count":3,"area":null},{"id":"2506.20128","title":"CCRS: A Zero-Shot LLM-as-a-Judge Framework for Comprehensive RAG Evaluation","created":"2025-06-25","cited_by_count":3,"area":"rag"},{"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":"2501.13567","title":"K-COMP: Retrieval-Augmented Medical Domain Question Answering With Knowledge-Injected Compressor","created":"2025-01-23","cited_by_count":2,"area":"rag"},{"id":"2503.23687","title":"MKA: Leveraging Cross-Lingual Consensus for Model Abstention","created":"2025-03-31","cited_by_count":2,"area":null},{"id":"2504.11197","title":"Efficient Distributed Retrieval-Augmented Generation for Enhancing Language Model Performance","created":"2025-04-15","cited_by_count":2,"area":"rag"},{"id":"2505.07917","title":"Efficient and Reproducible Biomedical Question Answering using Retrieval Augmented Generation","created":"2025-05-12","cited_by_count":2,"area":"rag"},{"id":"2505.14215","title":"Safety Degradation in AI Agents","created":"2025-05-20","cited_by_count":2,"area":"agents"},{"id":"2505.21870","title":"Evaluating the Retrieval Robustness of Large Language Models","created":"2025-05-28","cited_by_count":2,"area":"rag"},{"id":"2506.04583","title":"SUCEA: Reasoning-Intensive Retrieval for Adversarial Fact-checking through Claim Decomposition and Editing","created":"2025-06-05","cited_by_count":2,"area":"lr"},{"id":"2507.23541","title":"Med-R$^3$: Enhancing Medical Retrieval-Augmented Reasoning of LLMs via Progressive Reinforcement Learning","created":"2025-07-31","cited_by_count":2,"area":"lr"},{"id":"2508.11386","title":"Retrieval-augmented reasoning with lean language models","created":"2025-08-15","cited_by_count":2,"area":"lr"},{"id":"2405.04065","title":"FlashBack: Efficient Retrieval-Augmented Language Modeling for Fast Inference","created":"2024-05-07","cited_by_count":1,"area":"rag"},{"id":"2506.21288","title":"Small Encoders Can Rival Large Decoders in Detecting Groundedness","created":"2025-06-26","cited_by_count":1,"area":null},{"id":"2507.01900","title":"High-Layer Attention Pruning with Rescaling","created":"2025-07-02","cited_by_count":1,"area":null},{"id":"2604.18509","title":"MASS-RAG: Multi-Agent Synthesis Retrieval-Augmented Generation","created":"2026-04-20","cited_by_count":1,"area":"rag"},{"id":"2606.11474","title":"Mahalanobis-Guided Latent OOD Detection for Hybrid ES-DRL Control in Time-Varying Systems","created":"2026-06-09","cited_by_count":1,"area":null},{"id":"2408.09585","title":"On the Necessity of World Knowledge for Mitigating Missing Labels in Extreme Classification","created":"2024-08-18","cited_by_count":0,"area":null},{"id":"2503.14382","title":"Good/Evil Reputation Judgment of Celebrities by LLMs via Retrieval Augmented Generation","created":"2025-03-18","cited_by_count":0,"area":"rag"},{"id":"2505.18694","title":"AI-Driven Climate Policy Scenario Generation for Sub-Saharan Africa","created":"2025-05-24","cited_by_count":0,"area":null},{"id":"2508.02074","title":"The SMeL Test: A simple benchmark for media literacy in language models","created":"2025-08-04","cited_by_count":0,"area":null},{"id":"2511.04880","title":"DMA: Online RAG Alignment with Human Feedback","created":"2025-11-06","cited_by_count":0,"area":"rag"},{"id":"2601.20810","title":"Context-Augmented Code Generation Using Programming Knowledge Graphs","created":"2026-01-28","cited_by_count":0,"area":null},{"id":"2603.00172","title":"Hidden in the Metadata: Stealth Poisoning Attacks on Multimodal Retrieval-Augmented Generation","created":"2026-02-26","cited_by_count":0,"area":"mllm"},{"id":"2604.06097","title":"Masking or Mitigating? Deconstructing the Impact of Query Rewriting on Retriever Biases in RAG","created":"2026-04-07","cited_by_count":0,"area":"rag"},{"id":"2605.01407","title":"The Pre-Training Study of Expanded-SPLADE Models on Web Document Titles","created":"2026-05-02","cited_by_count":0,"area":null},{"id":"2608.01311","title":"RH-RAG: Trustworthy Long-Form Generation for Privacy-Constrained Settings","created":"2026-08-02","cited_by_count":0,"area":null}],"next_cursor":null}