{"total":22,"rows":[{"id":"2405.13576","title":"FlashRAG: A Modular Toolkit for Efficient Retrieval-Augmented Generation Research","created":"2024-05-22","cited_by_count":166,"area":"mllm"},{"id":"2404.18532","title":"MileBench: Benchmarking MLLMs in Long Context","created":"2024-04-29","cited_by_count":88,"area":"mllm"},{"id":"2308.04152","title":"Fine-tuning Multimodal LLMs to Follow Zero-shot Demonstrative Instructions","created":"2023-08-08","cited_by_count":77,"area":"mllm"},{"id":"2407.13766","title":"Visual Haystacks: A Vision-Centric Needle-In-A-Haystack Benchmark","created":"2024-07-18","cited_by_count":55,"area":"mllm"},{"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":"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":"2403.04735","title":"SnapNTell: Enhancing Entity-Centric Visual Question Answering with Retrieval Augmented Multimodal LLM","created":"2024-03-07","cited_by_count":18,"area":"mllm"},{"id":"2411.16740","title":"Document Haystacks: Vision-Language Reasoning Over Piles of 1000+ Documents","created":"2024-11-23","cited_by_count":17,"area":"mllm"},{"id":"2512.22748","title":"TrimTokenator-LC: Towards Adaptive Visual Token Pruning for Large Multimodal Models with Long Contexts","created":"2025-12-28","cited_by_count":14,"area":"mllm"},{"id":"2410.14154","title":"RA-BLIP: Multimodal Adaptive Retrieval-Augmented Bootstrapping Language-Image Pre-training","created":"2024-10-18","cited_by_count":3,"area":"mllm"},{"id":"2211.00262","title":"Training Vision-Language Models with Less Bimodal Supervision","created":"2022-11-01","cited_by_count":2,"area":"mllm"},{"id":"2508.17334","title":"Mind the (Language) Gap: Towards Probing Numerical and Cross-Lingual Limits of LVLMs","created":"2025-08-24","cited_by_count":2,"area":"mllm"},{"id":"2510.09266","title":"CFVBench: A Comprehensive Video Benchmark for Fine-grained Multimodal Retrieval-Augmented Generation","created":"2025-10-10","cited_by_count":2,"area":"mllm"},{"id":"2510.22694","title":"Windsock is Dancing: Adaptive Multimodal Retrieval-Augmented Generation","created":"2025-10-26","cited_by_count":1,"area":"mllm"},{"id":"2511.19969","title":"M$^3$Prune: Hierarchical Communication Graph Pruning for Efficient Multi-Modal Multi-Agent Retrieval-Augmented Generation","created":"2025-11-25","cited_by_count":1,"area":"mllm"},{"id":"2511.22141","title":"Bridging the Modality Gap by Similarity Standardization with Pseudo-Positive Samples","created":"2025-11-27","cited_by_count":1,"area":"mllm"},{"id":"2606.09578","title":"TABVERSE: Benchmarking Cross-Format Table Understanding in LLMs and VLMs","created":"2026-06-08","cited_by_count":1,"area":"mllm"},{"id":"2606.26079","title":"Same Evidence, Different Answer: Auditing Order Sensitivity in Multimodal Large Language Models","created":"2026-06-24","cited_by_count":1,"area":"mllm"},{"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":"2606.25343","title":"Invoice Haystack: Benchmarking Document Retrieval and Visual Question Answering Under Strong Visual Homogeneity","created":"2026-06-24","cited_by_count":0,"area":"mllm"},{"id":"2607.06649","title":"POPS: Recovering Unlearned Multi-Modality Knowledge in MLLMs with Prompt-Optimized Parameter Shaking","created":"2026-07-07","cited_by_count":0,"area":"mllm"},{"id":"2609.05518","title":"CrossModalQA: A Cross-modal and Multi-hop Benchmark for Multimodal Retrieval-augmented Generation","created":"2026-08-31","cited_by_count":0,"area":"mllm"}],"next_cursor":null}