{"total":135,"rows":[{"id":"2309.07864","title":"The Rise and Potential of Large Language Model Based Agents: A Survey","created":"2023-09-14","cited_by_count":1439,"area":"agents"},{"id":"2504.13958","title":"ToolRL: Reward is All Tool Learning Needs","created":"2025-04-16","cited_by_count":362,"area":"agents"},{"id":"2402.10978","title":"Language Models with Conformal Factuality Guarantees","created":"2024-02-15","cited_by_count":131,"area":null},{"id":"2408.04948","title":"HybridRAG: Integrating Knowledge Graphs and Vector Retrieval Augmented Generation for Efficient Information Extraction","created":"2024-08-09","cited_by_count":93,"area":"rag"},{"id":"2501.13958","title":"A Survey of Graph Retrieval-Augmented Generation for Customized Large Language Models","created":"2025-01-21","cited_by_count":88,"area":"rag"},{"id":"2405.15179","title":"VB-LoRA: Extreme Parameter Efficient Fine-Tuning with Vector Banks","created":"2024-05-24","cited_by_count":52,"area":null},{"id":"2408.07057","title":"A Survey on Model MoErging: Recycling and Routing Among Specialized Experts for Collaborative Learning","created":"2024-08-13","cited_by_count":52,"area":null},{"id":"2502.11435","title":"SMART: Self-Aware Agent for Tool Overuse Mitigation","created":"2025-02-17","cited_by_count":52,"area":"lr"},{"id":"2402.10189","title":"Uncertainty Quantification for In-Context Learning of Large Language Models","created":"2024-02-15","cited_by_count":45,"area":null},{"id":"2409.06857","title":"What is the Role of Small Models in the LLM Era: A Survey","created":"2024-09-10","cited_by_count":41,"area":null},{"id":"2403.03432","title":"Mixture-of-LoRAs: An Efficient Multitask Tuning for Large Language Models","created":"2024-03-06","cited_by_count":38,"area":"moe"},{"id":"2404.17729","title":"CoMM: Collaborative Multi-Agent, Multi-Reasoning-Path Prompting for Complex Problem Solving","created":"2024-04-26","cited_by_count":31,"area":"lr"},{"id":"2405.00465","title":"BiomedRAG: A Retrieval Augmented Large Language Model for Biomedicine","created":"2024-05-01","cited_by_count":31,"area":"rag"},{"id":"2307.16851","title":"Towards Trustworthy and Aligned Machine Learning: A Data-centric Survey with Causality Perspectives","created":"2023-07-31","cited_by_count":30,"area":"alignment"},{"id":"2310.04942","title":"Large Language Models for Spatial Trajectory Patterns Mining","created":"2023-10-07","cited_by_count":27,"area":null},{"id":"2307.15290","title":"ChatHome: Development and Evaluation of a Domain-Specific Language Model for Home Renovation","created":"2023-07-28","cited_by_count":25,"area":null},{"id":"2406.14833","title":"Efficient Continual Pre-training by Mitigating the Stability Gap","created":"2024-06-21","cited_by_count":25,"area":null},{"id":"2312.09007","title":"LLMind: Orchestrating AI and IoT with LLM for Complex Task Execution","created":"2023-12-14","cited_by_count":24,"area":null},{"id":"2402.12869","title":"Exploring the Impact of Table-to-Text Methods on Augmenting LLM-based Question Answering with Domain Hybrid Data","created":"2024-02-20","cited_by_count":24,"area":null},{"id":"2406.12034","title":"Self-MoE: Towards Compositional Large Language Models with Self-Specialized Experts","created":"2024-06-17","cited_by_count":23,"area":"moe"},{"id":"2404.09554","title":"Explainable Generative AI (GenXAI): A Survey, Conceptualization, and Research Agenda","created":"2024-04-15","cited_by_count":22,"area":null},{"id":"2410.03105","title":"Mamba in Vision: A Comprehensive Survey of Techniques and Applications","created":"2024-10-04","cited_by_count":18,"area":"ssm"},{"id":"2412.10047","title":"Large Action Models: From Inception to Implementation","created":"2024-12-13","cited_by_count":18,"area":null},{"id":"2501.11551","title":"PIKE-RAG: sPecIalized KnowledgE and Rationale Augmented Generation","created":"2025-01-20","cited_by_count":18,"area":"rag"},{"id":"2502.10990","title":"FinMTEB: Finance Massive Text Embedding Benchmark","created":"2025-02-16","cited_by_count":18,"area":null},{"id":"2405.13053","title":"MeteoRA: Multiple-tasks Embedded LoRA for Large Language Models","created":"2024-05-19","cited_by_count":16,"area":"moe"},{"id":"2409.19759","title":"Balancing Cost and Effectiveness of Synthetic Data Generation Strategies for LLMs","created":"2024-09-29","cited_by_count":15,"area":"synth"},{"id":"2502.11075","title":"Exposing Numeracy Gaps: A Benchmark to Evaluate Fundamental Numerical Abilities in Large Language Models","created":"2025-02-16","cited_by_count":14,"area":null},{"id":"2508.09494","title":"Learning Facts at Scale with Active Reading","created":"2025-08-13","cited_by_count":13,"area":null},{"id":"2409.18511","title":"Do We Need Domain-Specific Embedding Models? An Empirical Investigation","created":"2024-09-27","cited_by_count":12,"area":null},{"id":"2505.13033","title":"TSPulse: Tiny Pre-Trained Models with Disentangled Representations for Rapid Time-Series Analysis","created":"2025-05-19","cited_by_count":12,"area":null},{"id":"2509.01822","title":"When LLM Meets Time Series: Can LLMs Perform Multi-Step Time Series Reasoning and Inference","created":"2025-09-01","cited_by_count":12,"area":"lr"},{"id":"2401.02575","title":"Large Language Models for Social Networks: Applications, Challenges, and Solutions","created":"2024-01-04","cited_by_count":11,"area":null},{"id":"2407.01638","title":"LASSI: An LLM-based Automated Self-Correcting Pipeline for Translating Parallel Scientific Codes","created":"2024-06-30","cited_by_count":10,"area":null},{"id":"2406.10310","title":"TEG-DB: A Comprehensive Dataset and Benchmark of Textual-Edge Graphs","created":"2024-06-14","cited_by_count":9,"area":null},{"id":"2308.04913","title":"LLaMA-E: Empowering E-commerce Authoring with Object-Interleaved Instruction Following","created":"2023-08-09","cited_by_count":8,"area":null},{"id":"2309.03433","title":"Improving Open Information Extraction with Large Language Models: A Study on Demonstration Uncertainty","created":"2023-09-07","cited_by_count":8,"area":null},{"id":"2401.04471","title":"TransportationGames: Benchmarking Transportation Knowledge of (Multimodal) Large Language Models","created":"2024-01-09","cited_by_count":8,"area":"mllm"},{"id":"2403.05789","title":"ItD: Large Language Models Can Teach Themselves Induction through Deduction","created":"2024-03-09","cited_by_count":8,"area":null},{"id":"2410.04717","title":"$\\textbf{Only-IF}$:Revealing the Decisive Effect of Instruction Diversity on Generalization","created":"2024-10-07","cited_by_count":8,"area":null},{"id":"2506.00842","title":"Toward Structured Knowledge Reasoning: Contrastive Retrieval-Augmented Generation on Experience","created":"2025-06-01","cited_by_count":8,"area":"lr"},{"id":"2506.06301","title":"Large Language Models and Their Applications in Roadway Safety and Mobility Enhancement: A Comprehensive Review","created":"2025-05-19","cited_by_count":8,"area":null},{"id":"2509.25712","title":"Expert Merging: Model Merging with Unsupervised Expert Alignment and Importance-Guided Layer Chunking","created":"2025-09-30","cited_by_count":8,"area":"mllm"},{"id":"2401.00544","title":"A Reliable Knowledge Processing Framework for Combustion Science using Foundation Models","created":"2023-12-31","cited_by_count":7,"area":null},{"id":"2412.15298","title":"A Comparative Study of DSPy Teleprompter Algorithms for Aligning Large Language Models Evaluation Metrics to Human Evaluation","created":"2024-12-19","cited_by_count":7,"area":"alignment"},{"id":"2508.18880","title":"Challenges for Generative AI in Legal Reasoning","created":"2025-08-26","cited_by_count":7,"area":"lr"},{"id":"2312.12276","title":"POND: Multi-Source Time Series Domain Adaptation with Information-Aware Prompt Tuning","created":"2023-12-19","cited_by_count":6,"area":null},{"id":"2402.02357","title":"Multi-modal Causal Structure Learning and Root Cause Analysis","created":"2024-02-04","cited_by_count":6,"area":null},{"id":"2405.07745","title":"LlamaTurk: Adapting Open-Source Generative Large Language Models for Low-Resource Language","created":"2024-05-13","cited_by_count":6,"area":null},{"id":"2410.15308","title":"LlamaLens: Specialized Multilingual LLM for Analyzing News and Social Media Content","created":"2024-10-20","cited_by_count":6,"area":null},{"id":"2411.06824","title":"Combining Domain and Alignment Vectors to Achieve Better Knowledge-Safety Trade-offs in LLMs","created":"2024-11-11","cited_by_count":6,"area":null},{"id":"2508.09893","title":"RAGulating Compliance: A Multi-Agent Knowledge Graph for Regulatory QA","created":"2025-08-13","cited_by_count":6,"area":"agents"},{"id":"2508.16081","title":"CEQuest: Benchmarking Large Language Models for Construction Estimation","created":"2025-08-22","cited_by_count":6,"area":null},{"id":"2509.21155","title":"Learning the Wrong Lessons: Syntactic-Domain Spurious Correlations in Language Models","created":"2025-09-25","cited_by_count":6,"area":null},{"id":"2410.05097","title":"DreamSat: Towards a General 3D Model for Novel View Synthesis of Space Objects","created":"2024-10-07","cited_by_count":5,"area":null},{"id":"2505.01627","title":"A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components","created":"2025-05-02","cited_by_count":5,"area":null},{"id":"2505.05225","title":"QualBench: Benchmarking Chinese LLMs with Localized Professional Qualifications for Vertical Domain Evaluation","created":"2025-05-08","cited_by_count":5,"area":null},{"id":"2508.06555","title":"StyleTailor: Towards Personalized Fashion Styling via Hierarchical Negative Feedback","created":"2025-08-06","cited_by_count":5,"area":null},{"id":"2402.01758","title":"Aalap: AI Assistant for Legal & Paralegal Functions in India","created":"2024-01-30","cited_by_count":4,"area":null},{"id":"2407.06985","title":"PEER: Expertizing Domain-Specific Tasks with a Multi-Agent Framework and Tuning Methods","created":"2024-07-09","cited_by_count":4,"area":"rag"},{"id":"2408.00307","title":"ABC Align: Large Language Model Alignment for Safety & Accuracy","created":"2024-08-01","cited_by_count":4,"area":"alignment"},{"id":"2410.21868","title":"Improving In-Context Learning with Small Language Model Ensembles","created":"2024-10-29","cited_by_count":4,"area":null},{"id":"2412.14426","title":"All-in-One Tuning and Structural Pruning for Domain-Specific LLMs","created":"2024-12-19","cited_by_count":4,"area":null},{"id":"2402.01858","title":"Explaining latent representations of generative models with large multimodal models","created":"2024-02-02","cited_by_count":3,"area":"mllm"},{"id":"2402.10779","title":"A Condensed Transition Graph Framework for Zero-shot Link Prediction with Large Language Models","created":"2024-02-16","cited_by_count":3,"area":null},{"id":"2405.18292","title":"Semantic are Beacons: A Semantic Perspective for Unveiling Parameter-Efficient Fine-Tuning in Knowledge Learning","created":"2024-05-28","cited_by_count":3,"area":null},{"id":"2406.03614","title":"Advancing Anomaly Detection: Non-Semantic Financial Data Encoding with LLMs","created":"2024-06-05","cited_by_count":3,"area":null},{"id":"2411.14790","title":"KBAlign: Efficient Self Adaptation on Specific Knowledge Bases","created":"2024-11-22","cited_by_count":3,"area":"rag"},{"id":"2412.15891","title":"TelcoLM: collecting data, adapting, and benchmarking language models for the telecommunication domain","created":"2024-12-20","cited_by_count":3,"area":null},{"id":"2504.06426","title":"S'MoRE: Structural Mixture of Residual Experts for Parameter-Efficient LLM Fine-tuning","created":"2025-04-08","cited_by_count":3,"area":"moe"},{"id":"2509.07177","title":"Towards EnergyGPT: A Large Language Model Specialized for the Energy Sector","created":"2025-09-08","cited_by_count":3,"area":null},{"id":"2510.18908","title":"Improving Topic Modeling of Social Media Short Texts with Rephrasing: A Case Study of COVID-19 Related Tweets","created":"2025-10-21","cited_by_count":3,"area":null},{"id":"2607.25614","title":"MemSFT: Mitigating Alignment Tax with an External Parametric Memory","created":"2026-07-28","cited_by_count":3,"area":"alignment"},{"id":"2307.10930","title":"MediaGPT : A Large Language Model For Chinese Media","created":"2023-07-20","cited_by_count":2,"area":null},{"id":"2402.16977","title":"Dealing with Data for RE: Mitigating Challenges while using NLP and Generative AI","created":"2024-02-26","cited_by_count":2,"area":null},{"id":"2404.01785","title":"Can Humans Identify Domains?","created":"2024-04-02","cited_by_count":2,"area":null},{"id":"2406.05109","title":"Large Generative Graph Models","created":"2024-06-07","cited_by_count":2,"area":"diffusion"},{"id":"2408.11609","title":"Xinyu: An Efficient LLM-based System for Commentary Generation","created":"2024-08-21","cited_by_count":2,"area":null},{"id":"2410.06547","title":"TuringQ: Benchmarking AI Comprehension in Theory of Computation","created":"2024-10-09","cited_by_count":2,"area":"lr"},{"id":"2503.15055","title":"ELTEX: A Framework for Domain-Driven Synthetic Data Generation","created":"2025-03-19","cited_by_count":2,"area":"synth"},{"id":"2506.10330","title":"Augmenting Large Language Models with Static Code Analysis for Automated Code Quality Improvements","created":"2025-06-12","cited_by_count":2,"area":null},{"id":"2508.07353","title":"Benchmarking for Domain-Specific LLMs: A Case Study on Academia and Beyond","created":"2025-08-10","cited_by_count":2,"area":null},{"id":"2509.22725","title":"A Meta-Analysis of LLM Effects on Students across Qualification, Socialisation, and Subjectification","created":"2025-09-25","cited_by_count":2,"area":null},{"id":"2602.00597","title":"Hermes the Polyglot: A Unified Framework to Enhance Expressiveness for Multimodal Interlingual Subtitling","created":"2026-01-31","cited_by_count":2,"area":null},{"id":"2602.09319","title":"Benchmarking Knowledge-Extraction Attack and Defense on Retrieval-Augmented Generation","created":"2026-02-10","cited_by_count":2,"area":"rag"},{"id":"2603.02239","title":"Engineering Reasoning and Instruction (ERI) Benchmark: A Large Taxonomy-driven Dataset for Foundation Models and Agents","created":"2026-02-16","cited_by_count":2,"area":"lr"},{"id":"2604.10027","title":"SinkTrack: Attention Sink based Context Anchoring for Large Language Models","created":"2026-04-11","cited_by_count":2,"area":null},{"id":"2607.19604","title":"Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models","created":"2026-07-21","cited_by_count":2,"area":null},{"id":"2608.29966","title":"DataFoundry: Evolving Data Preparators via Recursive Self-Improvement","created":"2026-08-30","cited_by_count":2,"area":"synth"},{"id":"2401.00504","title":"HSC-GPT: A Large Language Model for Human Settlements Construction","created":"2023-12-31","cited_by_count":1,"area":null},{"id":"2405.11950","title":"WisPerMed at BioLaySumm: Adapting Autoregressive Large Language Models for Lay Summarization of Scientific Articles","created":"2024-05-20","cited_by_count":1,"area":null},{"id":"2405.19787","title":"From Symbolic Tasks to Code Generation: Diversification Yields Better Task Performers","created":"2024-05-30","cited_by_count":1,"area":null},{"id":"2408.13338","title":"LalaEval: A Holistic Human Evaluation Framework for Domain-Specific Large Language Models","created":"2024-08-23","cited_by_count":1,"area":null},{"id":"2411.11289","title":"LP Data Pipeline: Lightweight, Purpose-driven Data Pipeline for Large Language Models","created":"2024-11-18","cited_by_count":1,"area":null},{"id":"2411.11933","title":"METEOR: Evolutionary Journey of Large Language Models from Guidance to Self-Growth","created":"2024-11-18","cited_by_count":1,"area":null},{"id":"2412.15443","title":"SKETCH: Structured Knowledge Enhanced Text Comprehension for Holistic Retrieval","created":"2024-12-19","cited_by_count":1,"area":"rag"},{"id":"2506.00011","title":"Movable Antenna Enhanced Federated Fine-Tuning of Large Language Models via Hybrid Client Selection Optimization","created":"2025-05-16","cited_by_count":1,"area":null},{"id":"2507.06795","title":"ixi-GEN: Efficient Industrial sLLMs through Domain Adaptive Continual Pretraining","created":"2025-07-09","cited_by_count":1,"area":null},{"id":"2507.23440","title":"Self-Foveate: Enhancing Diversity and Difficulty of Synthesized Instructions from Unsupervised Text via Multi-Level Foveation","created":"2025-07-31","cited_by_count":1,"area":null},{"id":"2509.18226","title":"From \"What to Eat?\" to Perfect Recipe: ChefMind's Chain-of-Exploration for Ambiguous User Intent in Recipe Recommendation","created":"2025-09-22","cited_by_count":1,"area":null}],"next_cursor":"100"}