---
title: "Who cites Zifeng Wang — 371 papers of our library"
description: "371 papers of the Elamur Research library cite the works of Zifeng Wang, found in their bibliographies; the most cited first."
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---
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# Who cites Zifeng Wang

374 citations of their works from 371 papers of our library (of the 149,439 whose bibliographies we read) · 91 with a page here, the most cited first · [← Zifeng Wang](https://md.research.elamur.ai/free/en/authors/zifeng-wang/)

1. **[A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-hallucination-large-language-models/) [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/)**Lei Huang, Weijiang Yu, Weitao Ma, et al.*2023 · 3,231 citations*
2. **[Unifying Large Language Models and Knowledge Graphs: A Roadmap](https://md.research.elamur.ai/free/en/papers/pan-2023-unifying-large-language-models-knowledge/) [IEEE Transactions on Knowledge and Data Engineering](https://md.research.elamur.ai/free/en/venues/ieee-transactions-on-knowledge-and-data-engineering/)**Shirui Pan, Linhao Luo, Yufei Wang, et al.*2023 · 1,551 citations*
3. **[Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning](https://md.research.elamur.ai/free/en/papers/liu-2022-few-shot-parameter-efficient-fine/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Haokun Liu, Derek Tam, Mohammed Muqeeth, et al.*2022 · 754 citations*
4. [**A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications arXiv:2402.07927**Pranab Sahoo; Ayush Kumar Singh; Sriparna Saha; Vinija Jain; Samrat Mondal;, Aman Chadha*2024 · 375 citations*](https://md.research.elamur.ai/free/en/papers/sahoo-2024-systematic-survey-prompt-engineering-large/)
5. **[Graph Retrieval-Augmented Generation: A Survey](https://md.research.elamur.ai/free/en/papers/peng-2024-graph-retrieval-augmented-generation-survey/) [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/)**Boci Peng, Yun Zhu, Yongchao Liu, et al.*2024 · 276 citations*
6. **[HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models](https://md.research.elamur.ai/free/en/papers/gutierrez-2024-hipporag-neurobiologically-inspired-long-term/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Bernal Jimenez Gutierrez, Yiheng Shu, Yu Gu, et al.*2024 · 268 citations*
7. **[Large Language Models for Data Annotation and Synthesis: A Survey](https://md.research.elamur.ai/free/en/papers/tan-2024-large-language-models-data-annotation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhen Tan, Dawei Li, Song Wang, et al.*2024 · 262 citations*
8. [**Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey arXiv:2403.14608**Zeyu Han, Chao Gao, Jinyang Liu, et al.*2024 · 240 citations*](https://md.research.elamur.ai/free/en/papers/han-2024-parameter-efficient-fine-tuning-large/)
9. [**Debug like a Human: A Large Language Model Debugger via Verifying Runtime Execution Step-by-step arXiv:2402.16906**Li Zhong, Zilong Wang, Jingbo Shang*2024 · 124 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2024-debug-like-human-large-language/)
10. **[ATTEMPT: Parameter-Efficient Multi-task Tuning via Attentional Mixtures of Soft Prompts](https://md.research.elamur.ai/free/en/papers/asai-2022-attempt-parameter-efficient-multi-task/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Akari Asai, Mohammadreza Salehi, Matthew Peters, et al.*2022 · 122 citations*
11. [**Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models arXiv:2601.18734**Siyan Zhao, Zhihui Xie, Mengchen Liu, et al.*2026 · 97 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2026-self-distilled-reasoner-policy-self/)
12. [**AFlow: Automating Agentic Workflow Generation arXiv:2410.10762**Jiayi Zhang, Jinyu Xiang, Zhaoyang Yu, et al.*2024 · 95 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-aflow-automating-agentic-workflow/)
13. [**Retrieval-Augmented Generation with Graphs (GraphRAG) arXiv:2501.00309**Haoyu Han, Yu Wang, Harry Shomer, et al.*2025 · 87 citations*](https://md.research.elamur.ai/free/en/papers/han-2025-retrieval-augmented-generation-graphs-graphrag/)
14. [**Paths-over-Graph: Knowledge Graph Empowered Large Language Model Reasoning arXiv:2410.14211**Xingyu Tan, Xiaoyang Wang, Qing Liu, et al.*2024 · 80 citations*](https://md.research.elamur.ai/free/en/papers/tan-2024-paths-over-graph-knowledge-graph/)
15. [**A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well? arXiv:2503.24235**Qiyuan Zhang, Fuyuan Lyu, Zexu Sun, et al.*2025 · 79 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-survey-test-time-scaling-large/)
16. [**Exploring the Benefits of Training Expert Language Models over Instruction Tuning arXiv:2302.03202**Joel Jang, Seungone Kim, Seonghyeon Ye, et al.*2023 · 63 citations*](https://md.research.elamur.ai/free/en/papers/jang-2023-exploring-benefits-training-expert-language/)
17. **[S²R: Teaching LLMs to Self-verify and Self-correct via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/ma-2025-s-2-r-teaching-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruotian Ma, Peisong Wang, Cheng Liu, et al.*2025 · 26 citations*
18. **[Table-Critic: A Multi-Agent Framework for Collaborative Criticism and Refinement in Table Reasoning](https://md.research.elamur.ai/free/en/papers/yu-2025-table-critic-multi-agent-framework/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peiying Yu, Guoxin Chen, Jingjing Wang*2025 · 25 citations*
19. [**Baichuan-M1: Pushing the Medical Capability of Large Language Models arXiv:2502.12671**Bingning Wang, Haizhou Zhao, Huozhi Zhou, et al.*2025 · 24 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-baichuan-m1-pushing-medical/)
20. **[AI4Research: A Survey of Artificial Intelligence for Scientific Research](https://md.research.elamur.ai/free/en/papers/chen-2025-ai4research-survey-artificial-intelligence/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Mingda Yang, Libo Qin, et al.*2025 · 21 citations*
21. **[Beyond Chain-of-Thought: A Survey of Chain-of-X Paradigms for LLMs](https://md.research.elamur.ai/free/en/papers/xia-2025-beyond-chain-thought-survey-chain/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Yu Xia, Rui Wang, Xu Liu, et al.*2025 · 19 citations*
22. **[Search and Refine During Think: Facilitating Knowledge Refinement for Improved Retrieval-Augmented Reasoning](https://md.research.elamur.ai/free/en/papers/shi-2025-search-refine-during-think-facilitating/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yaorui Shi, Sihang Li, Chang Wu, et al.*2025 · 18 citations*
23. [**Improving Scientific Hypothesis Generation with Knowledge Grounded Large Language Models arXiv:2411.02382**Guangzhi Xiong, Eric Xie, Amir Hassan Shariatmadari, et al.*2024 · 16 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2024-improving-scientific-hypothesis-generation-knowledge/)
24. **[MAPoRL: Multi-Agent Post-Co-Training for Collaborative Large Language Models with Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/park-2025-maporl-multi-agent-post-co/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chanwoo Park, Seungju Han, Xingzhi Guo, et al.*2025 · 15 citations*
25. **[Ontology-Guided Reverse Thinking Makes Large Language Models Stronger on Knowledge Graph Question Answering](https://md.research.elamur.ai/free/en/papers/liu-2025-ontology-guided-reverse-thinking-makes/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Runxuan Liu, Bei Luo, Jiaqi Li, et al.*2025 · 15 citations*
26. **[Find Your Optimal Teacher: Personalized Data Synthesis via Router-Guided Multi-Teacher Distillation](https://md.research.elamur.ai/free/en/papers/zhang-2026-find-your-optimal-teacher-personalized/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hengyuan Zhang, Shiping Yang, Xiao Liang, et al.*2026 · 13 citations*
27. **[Learning from Diverse Reasoning Paths with Routing and Collaboration](https://md.research.elamur.ai/free/en/papers/lei-2025-learning-diverse-reasoning-paths-routing/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhenyu Lei, Zhen Tan, Song Wang, et al.*2025 · 11 citations*
28. **[BlindGuard: Safeguarding LLM-based Multi-Agent Systems under Unknown Attacks](https://md.research.elamur.ai/free/en/papers/miao-2026-blindguard-safeguarding-llm-based-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rui Miao, Yixin Liu, Yili Wang, et al.*2026 · 10 citations*
29. **[AnyMAC: Cascading Flexible Multi-Agent Collaboration via Next-Agent Prediction](https://md.research.elamur.ai/free/en/papers/wang-2025-anymac-cascading-flexible-multi-agent/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Song Wang, Zhen Tan, Zihan Chen, et al.*2025 · 10 citations*
30. **[RoT: Enhancing Table Reasoning with Iterative Row-Wise Traversals](https://md.research.elamur.ai/free/en/papers/zhang-2025-rot-enhancing-table-reasoning-iterative/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xuanliang Zhang, Dingzirui Wang, Keyan Xu, et al.*2025 · 10 citations*
31. [**100 Days After DeepSeek-R1: A Survey on Replication Studies and More Directions for Reasoning Language Models arXiv:2505.00551**Chong Zhang, Yue Deng, Xiang Lin, et al.*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-100-days-after-deepseek/)
32. **[TableLoRA: Low-rank Adaptation on Table Structure Understanding for Large Language Models](https://md.research.elamur.ai/free/en/papers/he-2025-tablelora-low-rank-adaptation-table/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinyi He, Yihao Liu, Mengyu Zhou, et al.*2025 · 8 citations*
33. **[MetaScale: Test-Time Scaling with Evolving Meta-Thoughts](https://md.research.elamur.ai/free/en/papers/liu-2026-metascale-test-time-scaling-evolving/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qin Liu, Wenxuan Zhou, Nan Xu, et al.*2026 · 7 citations*
34. **[TableEval: A Real-World Benchmark for Complex, Multilingual, and Multi-Structured Table Question Answering](https://md.research.elamur.ai/free/en/papers/zhu-2025-tableeval-real-world-benchmark-complex/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Junnan Zhu, Jingyi Wang, Bohan Yu, et al.*2025 · 7 citations*
35. [**Explain in Your Own Words: Improving Reasoning via Token-Selective Dual Knowledge Distillation arXiv:2603.13260**Minsang Kim, Seung Jun Baek*2026 · 6 citations*](https://md.research.elamur.ai/free/en/papers/kim-2026-explain-own-words-improving-reasoning/)
36. **[Sparse Logit Sampling: Accelerating Knowledge Distillation in LLMs](https://md.research.elamur.ai/free/en/papers/anshumann-2025-sparse-logit-sampling-accelerating-knowledge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Anshumann, Mohd Abbas Zaidi, Akhil Kedia, et al.*2025 · 6 citations*
37. **[Weaver: Interweaving SQL and LLM for Table Reasoning](https://md.research.elamur.ai/free/en/papers/khoja-2025-weaver-interweaving-sql-llm-table/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Rohit Khoja, Devanshu Gupta, Yanjie Fu, et al.*2025 · 6 citations*
38. **[GAM: Hierarchical Graph-based Agentic Memory for LLM Agents](https://md.research.elamur.ai/free/en/papers/wu-2026-gam-hierarchical-graph-based-agentic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhaofen Wu, Hanrong Zhang, Fulin Lin, et al.*2026 · 5 citations*
39. **[AutoGraph-R1: End-to-End Reinforcement Learning for Knowledge Graph Construction](https://md.research.elamur.ai/free/en/papers/tsang-2026-autograph-r1-end-end-reinforcement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hong Ting Tsang, Jiaxin Bai, Haoyu Huang, et al.*2026 · 4 citations*
40. **[When TableQA Meets Noise: A Dual Denoising Framework for Complex Questions and Large-scale Tables](https://md.research.elamur.ai/free/en/papers/ye-2026-when-tableqa-meets-noise-dual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shenghao Ye, Yu Guo, Dong Jin, et al.*2026 · 4 citations*
41. **[Which Reasoning Trajectories Teach Students to Reason Better? A Simple Metric of Informative Alignment](https://md.research.elamur.ai/free/en/papers/yang-2026-which-reasoning-trajectories-teach-students/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuming Yang, Mingyoung Lai, Wanxu Zhao, et al.*2026 · 4 citations*
42. **[From Storage to Experience: A Survey on the Evolution of LLM Agent Memory Mechanisms](https://md.research.elamur.ai/free/en/papers/luo-2026-storage-experience-survey-evolution-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jinghao Luo, Yuchen Tian, Chuxue Cao, et al.*2026 · 3 citations*
43. **[Metacognitive Self-Correction for Multi-Agent System via Prototype-Guided Next-Execution Reconstruction](https://md.research.elamur.ai/free/en/papers/shen-2026-metacognitive-self-correction-multi-agent/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xu Shen, Qi Zhang, Song Wang, et al.*2026 · 3 citations*
44. **[MMCLIP: Cross-Modal Attention Masked Modelling for Medical Language-Image Pre-Training](https://md.research.elamur.ai/free/en/papers/wu-2026-mmclip-cross-modal-attention-masked/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Biao Wu, Yutong Xie, Zeyu Zhang, et al.*2026 · 3 citations*
45. **[AdaMARP: An Adaptive Multi-Agent Interaction Framework for General Immersive Role-Playing](https://md.research.elamur.ai/free/en/papers/xu-2026-adamarp-adaptive-multi-agent-interaction/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhenhua Xu, Dongsheng Chen, Shuo Wang, et al.*2026 · 2 citations*
46. **[ClaimDB: A Fact Verification Benchmark over Large Structured Data](https://md.research.elamur.ai/free/en/papers/theologitis-2026-claimdb-fact-verification-benchmark-over/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Michael Theologitis, Preetam Prabhu Srikar Dammu, Chirag Shah, et al.*2026 · 2 citations*
47. **[Exploring Generative Process Reward Modeling for Semi-Structured Data: A Case Study of Table Question Answering](https://md.research.elamur.ai/free/en/papers/tang-2026-exploring-generative-process-reward-modeling/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Lei Tang, Wei Zhou, Mohsen Mesgar*2026 · 2 citations*
48. **[On-Policy Self-Distillation for Efficient Diffusion Language Models with Early-Stage Calibration](https://md.research.elamur.ai/free/en/papers/zhu-2026-policy-self-distillation-efficient-diffusion/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Huaisheng Zhu, MingYu Liu, Junze Liu, et al.*2026 · 2 citations*
49. **[Table Question Answering in the Era of Large Language Models: A Comprehensive Survey of Tasks, Methods, and Evaluation](https://md.research.elamur.ai/free/en/papers/zhou-2026-table-question-answering-era-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wei Zhou, Bolei Ma, Annemarie Friedrich, et al.*2026 · 2 citations*
50. [**AraTable: Benchmarking LLMs' Reasoning and Understanding of Arabic Tabular Data arXiv:2507.18442**Rana Alshaikh, Israa Alghanmi, Shelan Jeawak*2025 · 2 citations*](https://md.research.elamur.ai/free/en/papers/alshaikh-2025-aratable-benchmarking-llms-reasoning-understanding/)
51. **[Among Us: Measuring and Mitigating Malicious Contributions in Model Collaboration Systems](https://md.research.elamur.ai/free/en/papers/yang-2026-among-us-measuring-mitigating-malicious/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziyuan Yang, Wenxuan Ding, Shangbin Feng, et al.*2026 · 1 citation*
52. **[Building LLMs Like LEGO: Two-dimensional Architecture Reassembly of Large Language Models](https://md.research.elamur.ai/free/en/papers/wu-2026-building-llms-like-lego-two/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xingyu Wu, Yu Zhou, KC Tan*2026 · 1 citation*
53. **[CoReTab: Improving Multimodal Table Understanding with Code-driven Reasoning](https://md.research.elamur.ai/free/en/papers/nguyen-2026-coretab-improving-multimodal-table-understanding/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Van-Quang Nguyen, Takayuki Okatani*2026 · 1 citation*
54. **[Efficient Table Retrieval and Understanding with Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/xu-2026-efficient-table-retrieval-understanding-multimodal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhuoyan Xu, Haoyang Fang, Boran Han, et al.*2026 · 1 citation*
55. **[H-Mem: Hybrid Multi-Dimensional Memory Management for Long-Context Conversational Agents](https://md.research.elamur.ai/free/en/papers/ye-2026-h-mem-hybrid-multi-dimensional/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Zihe Ye, Jingyuan Huang, Weixin Chen, et al.*2026 · 1 citation*
56. **[Thinking Beyond the Local: Multi-View Instructed Adaptive Reasoning in KG-Enhanced LLMs](https://md.research.elamur.ai/free/en/papers/zhang-2026-thinking-beyond-local-multi-view/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Minghan Zhang, Shu Zhao, Zhen Yang, et al.*2026 · 1 citation*
57. **[A Survey of Large Language Model-Based Search Agents](https://md.research.elamur.ai/free/en/papers/xi-2026-survey-large-language-model-based/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yunjia Xi, Jianghao Lin, Yongzhao Xiao, et al.*2026*
58. **[Agent-Dice: Disentangling Knowledge Updates via Geometric Consensus for Agent Continual Learning](https://md.research.elamur.ai/free/en/papers/wu-2026-agent-dice-disentangling-knowledge-updates/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zheng Wu, Xingyu Lou, Xinbei Ma, et al.*2026*
59. **[Asking language models how to represent data for fine-tuning](https://md.research.elamur.ai/free/en/papers/singh-2026-asking-language-models-how-represent/) [Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era](https://md.research.elamur.ai/free/en/venues/surgellm/)**Usneek Singh, Ananya Singha, Abhijeet Awasthi, et al.*2026*
60. **[Balancing Knowledge Breadth and Task Depth for Effective Domain Adaptation Fine-Tuning](https://md.research.elamur.ai/free/en/papers/zhang-2026-balancing-knowledge-breadth-task-depth/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mu Zhang, Yuxiang Chu, Guangya Yu, et al.*2026*
61. **[BioVLM: Routing Prompts, Not Parameters, for Cross-Modality Generalization in Biomedical VLMs](https://md.research.elamur.ai/free/en/papers/singha-2026-biovlm-routing-prompts-not-parameters/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mainak Singha, Tanisha Gupta, Ankit Jha, et al.*2026*
62. **[Can LLMs Self-Correct Table Reasoning Errors?](https://md.research.elamur.ai/free/en/papers/shaikh-2026-can-llms-self-correct-table/) [Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era](https://md.research.elamur.ai/free/en/venues/surgellm/)**Farseen Shaikh*2026*
63. **[Context-Value-Action Architecture for Value-Driven Large Language Model Agents](https://md.research.elamur.ai/free/en/papers/zhang-2026-context-value-action-architecture-value/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**TianZe Zhang, Sirui Sun, Yuhang Xie, et al.*2026*
64. **[DarwinTOD: LLM-Driven Lifelong Self-evolution for Task-oriented Dialog Systems](https://md.research.elamur.ai/free/en/papers/zhang-2026-darwintod-llm-driven-lifelong-self/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shuyu Zhang, Yujie Liu, Xinru Wang, et al.*2026*
65. **[Dissecting GraphRAG: A Modular Analysis of Knowledge Structuring for Factoid Question Answering](https://md.research.elamur.ai/free/en/papers/nishida-2026-dissecting-graphrag-modular-analysis-knowledge/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Noriki Nishida, Rumana Ferdous Munne, Shanshan Liu, et al.*2026*
66. **[Learning How and What to Memorize: Cognition-Inspired Two-Stage Optimization for Evolving Memory](https://md.research.elamur.ai/free/en/papers/xu-2026-learning-how-what-memorize-cognition/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Derong Xu, Shuochen Liu, Pengfei Luo, et al.*2026*
67. **[MemBuilder: Reinforcing LLMs for Long-Term Memory Construction via Attributed Dense Rewards](https://md.research.elamur.ai/free/en/papers/shen-2026-membuilder-reinforcing-llms-long-term/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiyu Shen, Ziming Wu, Fuming Lai, et al.*2026*
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