{"total":28,"rows":[{"id":"2507.11412","title":"Seq vs Seq: An Open Suite of Paired Encoders and Decoders","created":"2025-07-15","cited_by_count":38,"area":null},{"id":"2605.13137","title":"LeanSearch v2: Global Premise Retrieval for Lean 4 Theorem Proving","created":"2026-05-13","cited_by_count":10,"area":null},{"id":"2509.26378","title":"MR$^2$-Bench: Going Beyond Matching to Reasoning in Multimodal Retrieval","created":"2025-09-30","cited_by_count":7,"area":null},{"id":"2602.21456","title":"Revisiting Text Ranking in Deep Research","created":"2026-02-25","cited_by_count":7,"area":null},{"id":"2605.15188","title":"FutureSim: Replaying World Events to Evaluate Adaptive Agents","created":"2026-05-14","cited_by_count":7,"area":null},{"id":"2509.07253","title":"Benchmarking Information Retrieval Models on Complex Retrieval Tasks","created":"2025-09-08","cited_by_count":6,"area":null},{"id":"2604.05306","title":"LLMs Should Express Uncertainty Explicitly","created":"2026-04-07","cited_by_count":6,"area":null},{"id":"2603.07392","title":"Can Large Language Models Keep Up? Benchmarking Online Adaptation to Continual Knowledge Streams","created":"2026-03-08","cited_by_count":5,"area":null},{"id":"2606.11780","title":"What Limits Does Quantization Place on Dense Top-$k$ Retrieval? A Theoretical Study","created":"2026-06-10","cited_by_count":4,"area":null},{"id":"2507.20783","title":"On The Role of Pretrained Language Models in General-Purpose Text Embeddings: A Survey","created":"2025-07-28","cited_by_count":3,"area":null},{"id":"2602.09839","title":"ARK: A Dual-Axis Multimodal Retrieval Benchmark along Reasoning and Knowledge","created":"2026-02-10","cited_by_count":3,"area":null},{"id":"2506.14345","title":"A Vision for Geo-Temporal Deep Research Systems: Towards Comprehensive, Transparent, and Reproducible Geo-Temporal Information Synthesis","created":"2025-06-17","cited_by_count":2,"area":null},{"id":"2606.07812","title":"Scaling Participation in Modular AI Systems","created":"2026-06-05","cited_by_count":2,"area":null},{"id":"2511.00444","title":"LIR: The First Workshop on Late Interaction and Multi Vector Retrieval @ ECIR 2026","created":"2025-11-01","cited_by_count":1,"area":null},{"id":"2606.13905","title":"ADORE: Iterative Query Expansion with Retrieval-Grounded Relevance Feedback","created":"2026-06-11","cited_by_count":1,"area":null},{"id":"2506.12637","title":"How Grounded is Wikipedia? A Study on Structured Evidential Support and Retrieval","created":"2025-06-14","cited_by_count":0,"area":null},{"id":"2509.07909","title":"Uncovering Scaling Laws for Large Language Models via Inverse Problems","created":"2025-09-09","cited_by_count":0,"area":null},{"id":"2509.16717","title":"Semi-Supervised Synthetic Data Generation with Fine-Grained Relevance Control for Short Video Search Relevance Modeling","created":"2025-09-20","cited_by_count":0,"area":null},{"id":"2510.18691","title":"Investigating LLM Capabilities on Long Context Comprehension for Medical Question Answering","created":"2025-10-21","cited_by_count":0,"area":null},{"id":"2602.01239","title":"Inferential Question Answering","created":"2026-02-01","cited_by_count":0,"area":null},{"id":"2603.17387","title":"CRE-T1 Preview Technical Report: Beyond Contrastive Learning for Reasoning-Intensive Retrieval","created":"2026-03-18","cited_by_count":0,"area":null},{"id":"2604.07201","title":"BRIDGE: Multimodal-to-Text Retrieval via Reinforcement-Learned Query Alignment","created":"2026-04-08","cited_by_count":0,"area":null},{"id":"2604.16576","title":"On the Robustness of LLM-Based Dense Retrievers: A Systematic Analysis of Generalizability and Stability","created":"2026-04-17","cited_by_count":0,"area":null},{"id":"2605.00400","title":"FollowTable: A Benchmark for Instruction-Following Table Retrieval","created":"2026-05-01","cited_by_count":0,"area":null},{"id":"2605.12370","title":"Context Convergence Improves Answering Inferential Questions","created":"2026-05-12","cited_by_count":0,"area":null},{"id":"2608.14107","title":"Retrieval Grounding Latent Reasoning for Dense Retrieval","created":"2026-08-14","cited_by_count":0,"area":null},{"id":"2608.30606","title":"Generative Retrieval for E-commerce: Jointly Learning Embedding and Codebook with Same Product Cluster","created":"2026-08-31","cited_by_count":0,"area":null},{"id":"2609.36359","title":"Better Nearest Neighbor Graph Indices via (Efficient) LLM-Guided Pruning","created":"2026-09-28","cited_by_count":0,"area":null}],"next_cursor":null}