{"total":45,"rows":[{"id":"2412.13663","title":"Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference","created":"2024-12-18","cited_by_count":554,"area":null},{"id":"2506.18902","title":"jina-embeddings-v4: Universal Embeddings for Multimodal Multilingual Retrieval","created":"2025-06-23","cited_by_count":76,"area":null},{"id":"2509.06888","title":"mmBERT: A Modern Multilingual Encoder with Annealed Language Learning","created":"2025-09-08","cited_by_count":45,"area":null},{"id":"2501.08828","title":"MMDocIR: Benchmarking Multimodal Retrieval for Long Documents","created":"2025-01-15","cited_by_count":43,"area":null},{"id":"2603.04370","title":"$\\tau$-Knowledge: Evaluating Conversational Agents over Unstructured Knowledge","created":"2026-03-04","cited_by_count":39,"area":null},{"id":"2412.01007","title":"CoRNStack: High-Quality Contrastive Data for Better Code Retrieval and Reranking","created":"2024-12-01","cited_by_count":37,"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":"2509.25085","title":"jina-reranker-v3: Last but Not Late Interaction for Listwise Document Reranking","created":"2025-09-29","cited_by_count":24,"area":null},{"id":"2505.07849","title":"SweRank: Software Issue Localization with Code Ranking","created":"2025-05-07","cited_by_count":20,"area":null},{"id":"2504.13128","title":"FreshStack: Building Realistic Benchmarks for Evaluating Retrieval on Technical Documents","created":"2025-04-17","cited_by_count":15,"area":null},{"id":"2508.21290","title":"Efficient Code Embeddings from Code Generation Models","created":"2025-08-29","cited_by_count":13,"area":null},{"id":"2603.19223","title":"F2LLM-v2: Inclusive, Performant, and Efficient Embeddings for a Multilingual World","created":"2026-03-19","cited_by_count":12,"area":null},{"id":"2411.01414","title":"A Deep Dive Into Large Language Model Code Generation Mistakes: What and Why?","created":"2024-11-03","cited_by_count":10,"area":null},{"id":"2506.08354","title":"Position: Text Embeddings Should Capture Implicit Semantics, Not Just Surface Meaning","created":"2025-06-10","cited_by_count":10,"area":null},{"id":"2605.27295","title":"Gemini Embedding 2: A Native Multimodal Embedding Model from Gemini","created":"2026-05-26","cited_by_count":10,"area":null},{"id":"2502.20204","title":"Granite Embedding Models","created":"2025-02-27","cited_by_count":8,"area":null},{"id":"2508.21085","title":"Granite Embedding R2 Models","created":"2025-08-26","cited_by_count":8,"area":null},{"id":"2602.19961","title":"Unlocking Multimodal Document Intelligence: From Current Triumphs to Future Frontiers of Visual Document Retrieval","created":"2026-02-23","cited_by_count":8,"area":null},{"id":"2505.15585","title":"MIRB: Mathematical Information Retrieval Benchmark","created":"2025-05-21","cited_by_count":6,"area":null},{"id":"2506.11066","title":"CoQuIR: A Comprehensive Benchmark for Code Quality-Aware Information Retrieval","created":"2025-05-31","cited_by_count":6,"area":null},{"id":"2506.12713","title":"Humanity's Last Code Exam: Can Advanced LLMs Conquer Human's Hardest Code Competition?","created":"2025-06-15","cited_by_count":6,"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":"2503.05860","title":"Benchmarking AI Models in Software Engineering: A Review, Search Tool, and Unified Approach for Elevating Benchmark Quality","created":"2025-03-07","cited_by_count":4,"area":null},{"id":"2505.24715","title":"CoRet: Improved Retriever for Code Editing","created":"2025-05-30","cited_by_count":3,"area":null},{"id":"2506.16552","title":"Revela: Dense Retriever Learning via Language Modeling","created":"2025-06-19","cited_by_count":3,"area":null},{"id":"2512.21332","title":"C2LLM Technical Report: A New Frontier in Code Retrieval via Adaptive Cross-Attention Pooling","created":"2025-12-24","cited_by_count":3,"area":null},{"id":"2507.12674","title":"ParaStudent: Closing the Sim2Real Gap in User Simulators for AI Tutor Evaluation","created":"2025-07-16","cited_by_count":2,"area":null},{"id":"2603.22008","title":"On the Challenges and Opportunities of Learned Sparse Retrieval for Code","created":"2026-03-23","cited_by_count":2,"area":null},{"id":"2505.12260","title":"LightRetriever: A LLM-based Text Retrieval Architecture with Extremely Faster Query Inference","created":"2025-05-18","cited_by_count":1,"area":null},{"id":"2509.16442","title":"Evaluating the Effectiveness and Scalability of LLM-Based Data Augmentation for Retrieval","created":"2025-09-19","cited_by_count":1,"area":null},{"id":"2512.10393","title":"Cross-modal Retrieval Models for Stripped Binary Analysis","created":"2025-12-11","cited_by_count":1,"area":null},{"id":"2512.23065","title":"TabiBERT: A Large-Scale ModernBERT Foundation Model and A Unified Benchmark for Turkish","created":"2025-12-28","cited_by_count":1,"area":null},{"id":"2601.21525","title":"LMK > CLS: Landmark Pooling for Dense Embeddings","created":"2026-01-29","cited_by_count":1,"area":null},{"id":"2605.04615","title":"Beyond Retrieval: A Multitask Benchmark and Model for Code Search","created":"2026-05-06","cited_by_count":1,"area":null},{"id":"2503.05315","title":"LoRACode: LoRA Adapters for Code Embeddings","created":"2025-03-07","cited_by_count":0,"area":null},{"id":"2507.20718","title":"Uncertainty-driven Embedding Convolution","created":"2025-07-28","cited_by_count":0,"area":null},{"id":"2509.25716","title":"DeepCodeSeek: Real-Time API Retrieval for Context-Aware Code Generation","created":"2025-09-30","cited_by_count":0,"area":null},{"id":"2510.18940","title":"NeuroAda: Activating Each Neuron's Potential for Parameter-Efficient Fine-Tuning","created":"2025-10-21","cited_by_count":0,"area":null},{"id":"2605.08299","title":"Do not copy and paste! Rewriting strategies for code retrieval","created":"2026-05-08","cited_by_count":0,"area":null},{"id":"2605.15081","title":"ML-Embed: Inclusive and Efficient Embeddings for a Multilingual World","created":"2026-05-14","cited_by_count":0,"area":null},{"id":"2606.01304","title":"When Hard Negatives Hurt: Bridging the Generative-Discriminative Gap in Hard Negative Synthesis for Retrieval","created":"2026-05-31","cited_by_count":0,"area":null},{"id":"2607.05443","title":"Scientific Code Search at Scale: A Multi-Domain Dataset and Benchmark","created":"2026-07-03","cited_by_count":0,"area":null},{"id":"2607.13311","title":"Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval","created":"2026-07-14","cited_by_count":0,"area":null},{"id":"2608.19957","title":"Natural Language Code Retrieval for 1C:Enterprise: An Open Benchmark and Efficient Bi-Encoder","created":"2026-08-20","cited_by_count":0,"area":null},{"id":"2610.19157","title":"DivAlgo: A systematic evaluation of algorithmic diversity for code generation models","created":"2026-10-13","cited_by_count":0,"area":null}],"next_cursor":null}