---
title: "Who cites Jheng-Hong Yang — 317 papers of our library"
description: "317 papers of the Elamur Research library cite the works of Jheng-Hong Yang, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/jheng-hong-yang/cited-by/"
---
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# Who cites Jheng-Hong Yang

375 citations of their works from 317 papers of our library (of the 149,439 whose bibliographies we read) · 63 with a page here, the most cited first · [← Jheng-Hong Yang](https://md.research.elamur.ai/free/en/authors/jheng-hong-yang/)

1. [**M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation arXiv:2402.03216**Jianlv Chen, Shitao Xiao, Peitian Zhang, et al.*2024 · 1,196 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-m3-embedding-multi-linguality/)
2. **[FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation](https://md.research.elamur.ai/free/en/papers/min-2023-factscore-fine-grained-atomic-evaluation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Sewon Min, Kalpesh Krishna, Xinxi Lyu, et al.*2023 · 987 citations*
3. [**Unsupervised Dense Information Retrieval with Contrastive Learning arXiv:2112.09118**Gautier Izacard, Mathilde Caron, Lucas Hosseini, et al.*2021 · 836 citations*](https://md.research.elamur.ai/free/en/papers/izacard-2021-unsupervised-dense-information-retrieval-contrastive/)
4. **[In-Context Retrieval-Augmented Language Models](https://md.research.elamur.ai/free/en/papers/ram-2023-context-retrieval-augmented-language-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ori Ram, Yoav Levine, Itay Dalmedigos, et al.*2023 · 793 citations*
5. **[Precise Zero-Shot Dense Retrieval without Relevance Labels](https://md.research.elamur.ai/free/en/papers/gao-2022-precise-zero-shot-dense-retrieval/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Luyu Gao, Xueguang Ma, Jimmy Lin, et al.*2022 · 549 citations*
6. **[ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction](https://md.research.elamur.ai/free/en/papers/santhanam-2022-colbertv2-effective-efficient-retrieval-lightweight/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Keshav Santhanam, Omar Khattab, Jon Saad-Falcon, et al.*2022 · 485 citations*
7. **[Benchmarking Retrieval-Augmented Generation for Medicine](https://md.research.elamur.ai/free/en/papers/xiong-2024-benchmarking-retrieval-augmented-generation-medicine/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Guangzhi Xiong, Qiao Jin, Zhiyong Lu, et al.*2024 · 430 citations*
8. **[Query2doc: Query Expansion with Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2023-query2doc-query-expansion-large-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Liang Wang, Nan Yang, Furu Wei*2023 · 354 citations*
9. [**Text and Code Embeddings by Contrastive Pre-Training arXiv:2201.10005**Arvind Neelakantan, Tao Xu, Raul Puri, et al.*2022 · 323 citations*](https://md.research.elamur.ai/free/en/papers/neelakantan-2022-text-code-embeddings-contrastive-pre/)
10. **[Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting](https://md.research.elamur.ai/free/en/papers/qin-2024-large-language-models-are-effective/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhen Qin, Rolf Jagerman, Kai Hui, et al.*2024 · 300 citations*
11. [**Large Dual Encoders Are Generalizable Retrievers arXiv:2112.07899**Jianmo Ni, Chen Qu, Jing Lu, et al.*2021 · 279 citations*](https://md.research.elamur.ai/free/en/papers/ni-2021-large-dual-encoders-generalizable-retrievers/)
12. [**BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models NeurIPS 2021 Datasets and Benchmarks**Nandan Thakur, Nils Reimers, Andreas Rücklé, et al.*2021 · 265 citations*](https://md.research.elamur.ai/free/en/papers/thakur-2021-beir-heterogenous-benchmark-zero/)
13. **[Fine-Tuning LLaMA for Multi-Stage Text Retrieval](https://md.research.elamur.ai/free/en/papers/ma-2023-fine-tuning-llama-multi-stage/) [International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)](https://md.research.elamur.ai/free/en/venues/international-acm-sigir-conference-on-research-and-development-in-information/)**Xueguang Ma, Liang Wang, Nan Yang, et al.*2023 · 257 citations*
14. **[RocketQAv2: A Joint Training Method for Dense Passage Retrieval and Passage Re-ranking](https://md.research.elamur.ai/free/en/papers/ren-2021-rocketqav2-joint-training-method-dense/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ruiyang Ren, Yingqi Qu, Jing Liu, et al.*2021 · 256 citations*
15. **[Improving Passage Retrieval with Zero-Shot Question Generation](https://md.research.elamur.ai/free/en/papers/sachan-2022-improving-passage-retrieval-zero-shot/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Devendra Sachan, Mike Lewis, Mandar Joshi, et al.*2022 · 199 citations*
16. **[Tool Learning with Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/qu-2024-tool-learning-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Changle Qu, Sunhao Dai, Xiaochi Wei, et al.*2024 · 195 citations*
17. [**SGPT: GPT Sentence Embeddings for Semantic Search arXiv:2202.08904**Niklas Muennighoff*2022 · 189 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2022-sgpt-gpt-sentence-embeddings-semantic/)
18. **[Evaluating Retrieval Quality in Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/salemi-2024-evaluating-retrieval-quality-retrieval-augmented/) [International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)](https://md.research.elamur.ai/free/en/venues/international-acm-sigir-conference-on-research-and-development-in-information/)**Alireza Salemi, Hamed Zamani*2024 · 181 citations*
19. **[On the Risk of Misinformation Pollution with Large Language Models](https://md.research.elamur.ai/free/en/papers/pan-2023-risk-misinformation-pollution-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yikang Pan, Liangming Pan, Wenhu Chen, et al.*2023 · 179 citations*
20. [**Promptagator: Few-shot Dense Retrieval From 8 Examples arXiv:2209.11755**Zhuyun Dai, Vincent Y. Zhao, Ji Ma, et al.*2022 · 170 citations*](https://md.research.elamur.ai/free/en/papers/dai-2022-promptagator-few-shot-dense-retrieval/)
21. **[GPL: Generative Pseudo Labeling for Unsupervised Domain Adaptation of Dense Retrieval](https://md.research.elamur.ai/free/en/papers/wang-2022-gpl-generative-pseudo-labeling-unsupervised/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Kexin Wang, Nandan Thakur, Nils Reimers, et al.*2022 · 155 citations*
22. **[Searching for Best Practices in Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/wang-2024-searching-best-practices-retrieval-augmented/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xiaohua Wang, Zhenghua Wang, Xuan Gao, et al.*2024 · 150 citations*
23. **[MIRACL: A Multilingual Retrieval Dataset Covering 18 Diverse Languages](https://md.research.elamur.ai/free/en/papers/zhang-2023-miracl-multilingual-retrieval-dataset-covering/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Xinyu Zhang, Nandan Thakur, Odunayo Ogundepo, et al.*2023 · 149 citations*
24. **[Fact-Checking Complex Claims with Program-Guided Reasoning](https://md.research.elamur.ai/free/en/papers/pan-2023-fact-checking-complex-claims-program/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Liangming Pan, Xiaobao Wu, Xinyuan Lu, et al.*2023 · 146 citations*
25. [**Rethinking with Retrieval: Faithful Large Language Model Inference arXiv:2301.00303**Hangfeng He, Hongming Zhang, Dan Roth*2023 · 143 citations*](https://md.research.elamur.ai/free/en/papers/he-2023-rethinking-retrieval-faithful-large-language/)
26. **[Mr. TyDi: A Multi-lingual Benchmark for Dense Retrieval](https://md.research.elamur.ai/free/en/papers/zhang-2021-mr-tydi-multi-lingual-benchmark/) [Workshop on Multilingual Representation Learning](https://md.research.elamur.ai/free/en/venues/mrl/)**Xinyu Zhang, Xueguang Ma, Peng Shi, et al.*2021 · 129 citations*
27. [**Knowledge-Augmented Language Model Prompting for Zero-Shot Knowledge Graph Question Answering arXiv:2306.04136**Jinheon Baek, Alham Fikri Aji, Amir Saffari*2023 · 119 citations*](https://md.research.elamur.ai/free/en/papers/baek-2023-knowledge-augmented-language-model-prompting/)
28. **[How to Train Your Dragon: Diverse Augmentation Towards Generalizable Dense Retrieval](https://md.research.elamur.ai/free/en/papers/lin-2023-how-train-your-dragon-diverse/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sheng-Chieh Lin, Akari Asai, Minghan Li, et al.*2023 · 116 citations*
29. **[Learning to Retrieve In-Context Examples for Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2024-learning-retrieve-context-examples-large/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Liang Wang, Nan Yang, Furu Wei*2024 · 106 citations*
30. **[SimLM: Pre-training with Representation Bottleneck for Dense Passage Retrieval](https://md.research.elamur.ai/free/en/papers/wang-2023-simlm-pre-training-representation-bottleneck/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Liang Wang, Nan Yang, Xiaolong Huang, et al.*2023 · 106 citations*
31. [**Zero-Shot Listwise Document Reranking with a Large Language Model arXiv:2305.02156**Xueguang Ma, Xinyu Zhang, Ronak Pradeep, et al.*2023 · 105 citations*](https://md.research.elamur.ai/free/en/papers/ma-2023-zero-shot-listwise-document-reranking/)
32. **[Parallel Context Windows for Large Language Models](https://md.research.elamur.ai/free/en/papers/ratner-2023-parallel-context-windows-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nir Ratner, Yoav Levine, Yonatan Belinkov, et al.*2023 · 102 citations*
33. [**SPLADE v2: Sparse Lexical and Expansion Model for Information Retrieval arXiv:2109.10086**Thibault Formal, Carlos Lassance, Benjamin Piwowarski, et al.*2021 · 83 citations*](https://md.research.elamur.ai/free/en/papers/formal-2021-splade-v2-sparse-lexical/)
34. [**RankVicuna: Zero-Shot Listwise Document Reranking with Open-Source Large Language Models arXiv:2309.15088**Ronak Pradeep, Sahel Sharifymoghaddam, Jimmy Lin*2023 · 81 citations*](https://md.research.elamur.ai/free/en/papers/pradeep-2023-rankvicuna-zero-shot-listwise-document/)
35. [**FlashRAG: A Modular Toolkit for Efficient Retrieval-Augmented Generation Research arXiv:2405.13576**Jiajie Jin, Yutao Zhu, Guanting Dong, et al.*2024 · 77 citations*](https://md.research.elamur.ai/free/en/papers/jin-2024-flashrag-modular-toolkit-efficient-retrieval/)
36. [**InPars: Data Augmentation for Information Retrieval using Large Language Models arXiv:2202.05144**Luiz Bonifacio, Hugo Abonizio, Marzieh Fadaee, et al.*2022 · 72 citations*](https://md.research.elamur.ai/free/en/papers/bonifacio-2022-inpars-data-augmentation-information-retrieval/)
37. **[Unifying Multimodal Retrieval via Document Screenshot Embedding](https://md.research.elamur.ai/free/en/papers/ma-2024-unifying-multimodal-retrieval-document-screenshot/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xueguang Ma, Sheng-Chieh Lin, Minghan Li, et al.*2024 · 61 citations*
38. **[The ROOTS Search Tool: Data Transparency for LLMs](https://md.research.elamur.ai/free/en/papers/piktus-2023-roots-search-tool-data-transparency/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Aleksandra Piktus, Christopher Akiki, Paulo Villegas, et al.*2023 · 42 citations*
39. **[BIDER: Bridging Knowledge Inconsistency for Efficient Retrieval-Augmented LLMs via Key Supporting Evidence](https://md.research.elamur.ai/free/en/papers/jin-2024-bider-bridging-knowledge-inconsistency-efficient/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiajie Jin, Yutao Zhu, Yujia Zhou, et al.*2024 · 28 citations*
40. **[MegaPairs: Massive Data Synthesis for Universal Multimodal Retrieval](https://md.research.elamur.ai/free/en/papers/zhou-2025-megapairs-massive-data-synthesis-universal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junjie Zhou, Yongping Xiong, Zheng Liu, et al.*2025 · 26 citations*
41. [**Large Language Models are Strong Zero-Shot Retriever arXiv:2304.14233**Tao Shen, Guodong Long, Xiubo Geng, et al.*2023 · 26 citations*](https://md.research.elamur.ai/free/en/papers/shen-2023-large-language-models-strong-zero/)
42. **[Developing a Pragmatic Benchmark for Assessing Korean Legal Language Understanding in Large Language Models](https://md.research.elamur.ai/free/en/papers/kim-2024-developing-pragmatic-benchmark-assessing-korean/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yeeun Kim, Youngrok Choi, Eunkyung Choi, et al.*2024 · 24 citations*
43. **[Evaluating Token-Level and Passage-Level Dense Retrieval Models for Math Information Retrieval](https://md.research.elamur.ai/free/en/papers/zhong-2022-evaluating-token-level-passage-level/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wei Zhong, Jheng-Hong Yang, Yuqing Xie, et al.*2022 · 23 citations*
44. **[Cross-document Event Coreference Search: Task, Dataset and Modeling](https://md.research.elamur.ai/free/en/papers/eirew-2022-cross-document-event-coreference-search/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Alon Eirew, Avi Caciularu, Ido Dagan*2022 · 15 citations*
45. **[RaDeR: Reasoning-aware Dense Retrieval Models](https://md.research.elamur.ai/free/en/papers/das-2025-rader-reasoning-aware-dense-retrieval/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Debrup Das, Sam O'Nuallain, Razieh Rahimi*2025 · 14 citations*
46. **[A Semantic Search Engine for Mathlib4](https://md.research.elamur.ai/free/en/papers/gao-2024-semantic-search-engine-mathlib4/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Guoxiong Gao, Haocheng Ju, Jiedong Jiang, et al.*2024 · 14 citations*
47. **[A Symbolic Framework for Evaluating Mathematical Reasoning and Generalisation with Transformers](https://md.research.elamur.ai/free/en/papers/meadows-2024-symbolic-framework-evaluating-mathematical-reasoning/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Jordan Meadows, Marco Valentino, Damien Teney, et al.*2024 · 14 citations*
48. **[Alignment for Efficient Tool Calling of Large Language Models](https://md.research.elamur.ai/free/en/papers/xu-2025-alignment-efficient-tool-calling-large/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hongshen Xu, Zihan Wang, Zichen Zhu, et al.*2025 · 13 citations*
49. **[s3: You Don't Need That Much Data to Train a Search Agent via RL](https://md.research.elamur.ai/free/en/papers/jiang-2025-s3-you-don-t-need/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Pengcheng Jiang, Xueqiang Xu, Jiacheng Lin, et al.*2025 · 12 citations*
50. **[AdaCQR: Enhancing Query Reformulation for Conversational Search via Sparse and Dense Retrieval Alignment](https://md.research.elamur.ai/free/en/papers/lai-2025-adacqr-enhancing-query-reformulation-conversational/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Yilong Lai, Jialong Wu, Congzhi Zhang, et al.*2025 · 9 citations*
51. **[Enhancing Systematic Decompositional Natural Language Inference Using Informal Logic](https://md.research.elamur.ai/free/en/papers/weir-2024-enhancing-systematic-decompositional-natural-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Nathaniel Weir, Kate Sanders, Orion Weller, et al.*2024 · 7 citations*
52. **[AuRED: Enabling Arabic Rumor Verification using Evidence from Authorities over Twitter](https://md.research.elamur.ai/free/en/papers/haouari-2024-aured-enabling-arabic-rumor-verification/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Fatima Haouari, Tamer Elsayed, Reem Suwaileh*2024 · 5 citations*
53. **[Multimodal Item Scoring for Natural Language Recommendation via Gaussian Process Regression with LLM Relevance Judgments](https://md.research.elamur.ai/free/en/papers/liu-2026-multimodal-item-scoring-natural-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yifan Simon Liu, Qianfeng Wen, Jiazhou Liang, et al.*2026 · 4 citations*
54. **[More Than Efficiency: Embedding Compression Improves Domain Adaptation in Dense Retrieval](https://md.research.elamur.ai/free/en/papers/zuo-2026-more-than-efficiency-embedding-compression/) [Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era](https://md.research.elamur.ai/free/en/venues/surgellm/)**Chunsheng Zuo, Daniel Khashabi*2026 · 2 citations*
55. **[ArTrivia: Harvesting Arabic Wikipedia to Build A New Arabic Question Answering Dataset](https://md.research.elamur.ai/free/en/papers/alrowili-2023-artrivia-harvesting-arabic-wikipedia-build/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Sultan Alrowili, K Vijay-Shanker*2023 · 2 citations*
56. **[QueStER: Query Specification for Generative Keyword-Based Retrieval](https://md.research.elamur.ai/free/en/papers/satouf-2026-quester-query-specification-generative-keyword/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Arthur Satouf, Yuxuan Zong, Habiboulaye Amadou Boubacar, et al.*2026 · 1 citation*
57. **[On Reference (In-)Determinacy in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/chen-2025-reference-determinacy-natural-language-inference/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sihao Chen, Chaitanya Malaviya, Alex Fabrikant, et al.*2025 · 1 citation*
58. **[CodeRise: Bootstrapping LLMs for Ultra Low-Resource Programming Languages via Progressive Self-Refinement Curriculum](https://md.research.elamur.ai/free/en/papers/wen-2026-coderise-bootstrapping-llms-ultra-low/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tengfei Wen, Xuanang Chen, Ben He, et al.*2026*
59. **[GroupRank: A Groupwise Paradigm for Effective and Efficient Passage Reranking with LLMs](https://md.research.elamur.ai/free/en/papers/long-2026-grouprank-groupwise-paradigm-effective-efficient/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Meixiu Long, Duolin Sun, Dan Yang, et al.*2026*
60. **[Improving Retrieval-Augmented Generation without Taxonomy-based Error Categorization](https://md.research.elamur.ai/free/en/papers/zhang-2026-improving-retrieval-augmented-generation-without/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Gongbo Zhang, Yifan Peng, Chunhua Weng*2026*
61. **[Let Retrievers Think Before Action: Thought-Augmented Embedding for Dense Retrieval](https://md.research.elamur.ai/free/en/papers/yan-2026-let-retrievers-think-before-action/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ruiran Yan, Wen Xiong, Ze Liu, et al.*2026*
62. **[Negative Sampling Techniques in Dense Retrieval: A Survey](https://md.research.elamur.ai/free/en/papers/wischounig-2026-negative-sampling-techniques-dense-retrieval/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Laurin Wischounig, Abdelrahman Abdallah, Adam Jatowt*2026*
63. **[Test-Time Training for Zero-Resource Dense Retrieval Reranking](https://md.research.elamur.ai/free/en/papers/liu-2026-test-time-training-zero-resource/) [Workshop on Towards Knowledgeable Foundation Models](https://md.research.elamur.ai/free/en/venues/knowfm/)**Shiyan Liu, Yichen Li*2026*

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