---
title: "Who cites Finetuned Language — page 4 — 1,887 citing papers"
description: "1,887 papers of the Elamur Research library cite «Finetuned Language Models Are Zero-Shot Learners», found in their bibliographies · page…"
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# Who cites «Finetuned Language Models Are Zero-Shot Learners»

1,887 papers of our library cite it (of the 149,439 whose bibliographies we read) · 499 with a page here, the most cited first · page 4 of 5 · 301–400 · [← back to «Finetuned Language Models Are Zero-Shot Learners»](https://md.research.elamur.ai/free/en/papers/wei-2021-finetuned-language-models-zero-shot/)

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301. [**Superfiltering: Weak-to-Strong Data Filtering for Fast Instruction-Tuning arXiv:2402.00530**Ming Li, Yong Zhang, Shwai He, et al.*2024 · 60 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-superfiltering-weak-strong-data-filtering/)
302. **[TARJAMAT: Evaluation of Bard and ChatGPT on Machine Translation of Ten Arabic Varieties](https://md.research.elamur.ai/free/en/papers/kadaoui-2023-tarjamat-evaluation-bard-chatgpt-machine/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Karima Kadaoui, Samar M. Magdy, Abdul Waheed, et al.*2023 · 60 citations*
303. **[Instruction Pre-Training: Language Models are Supervised Multitask Learners](https://md.research.elamur.ai/free/en/papers/cheng-2024-instruction-pre-training-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Daixuan Cheng, Yuxian Gu, Shaohan Huang, et al.*2024 · 59 citations*
304. **[ChatQA: Surpassing GPT-4 on Conversational QA and RAG](https://md.research.elamur.ai/free/en/papers/liu-2024-chatqa-surpassing-gpt-4-conversational/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zihan Liu, Wei Ping, Rajarshi Roy, et al.*2024 · 58 citations*
305. [**EduChat: A Large-Scale Language Model-based Chatbot System for Intelligent Education arXiv:2308.02773**Yuhao Dan, Zhikai Lei, Yiyang Gu, et al.*2023 · 58 citations*](https://md.research.elamur.ai/free/en/papers/dan-2023-educhat-large-scale-language-model/)
306. [**LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning arXiv:2308.03303**Longteng Zhang, Lin Zhang, Shaohuai Shi, et al.*2023 · 58 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-lora-fa-efficient-effective-low/)
307. [**MMICL: Empowering Vision-language Model with Multi-Modal In-Context Learning arXiv:2309.07915**Haozhe Zhao, Zefan Cai, Shuzheng Si, et al.*2023 · 58 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-mmicl-empowering-vision-language-model/)
308. **[Hello Again! LLM-powered Personalized Agent for Long-term Dialogue](https://md.research.elamur.ai/free/en/papers/li-2025-hello-again-llm-powered-personalized/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Hao Li, Chenghao Yang, An Zhang, et al.*2025 · 55 citations*
309. **[SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages](https://md.research.elamur.ai/free/en/papers/lovenia-2024-seacrowd-multilingual-multimodal-data-hub/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Holy Lovenia, Rahmad Mahendra, Salsabil Maulana Akbar, et al.*2024 · 54 citations*
310. [**Can Long-Context Language Models Subsume Retrieval, RAG, SQL, and More? arXiv:2406.13121**Jinhyuk Lee, Anthony Chen, Zhuyun Dai, et al.*2024 · 53 citations*](https://md.research.elamur.ai/free/en/papers/lee-2024-long-context-language-models-subsume/)
311. **[The Learnability of In-Context Learning](https://md.research.elamur.ai/free/en/papers/wies-2023-learnability-context-learning/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Noam Wies, Yoav Levine, Amnon Shashua*2023 · 53 citations*
312. [**Large Language Models are In-Context Semantic Reasoners rather than Symbolic Reasoners arXiv:2305.14825**Xiaojuan Tang, Zilong Zheng, Jiaqi Li, et al.*2023 · 52 citations*](https://md.research.elamur.ai/free/en/papers/tang-2023-large-language-models-context-semantic/)
313. [**WebLINX: Real-World Website Navigation with Multi-Turn Dialogue arXiv:2402.05930**Xing Han Lu, Zden\vek Kasner, Siva Reddy*2024 · 50 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-weblinx-real-world-website-navigation/)
314. [**TIGERScore: Towards Building Explainable Metric for All Text Generation Tasks arXiv:2310.00752**Dongfu Jiang, Yishan Li, Ge Zhang, et al.*2023 · 50 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2023-tigerscore-towards-building-explainable-metric/)
315. **[The Effectiveness of LLMs as Annotators: A Comparative Overview and Empirical Analysis of Direct Representation](https://md.research.elamur.ai/free/en/papers/pavlovic-2024-effectiveness-llms-annotators-comparative-overview/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Maja Pavlovic, Massimo Poesio*2024 · 49 citations*
316. **[The Multilingual Alignment Prism: Aligning Global and Local Preferences to Reduce Harm](https://md.research.elamur.ai/free/en/papers/aakanksha-2024-multilingual-alignment-prism-aligning-global/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Aakanksha, Arash Ahmadian, Beyza Ermis, et al.*2024 · 49 citations*
317. **[Mitigating Hallucinations and Off-target Machine Translation with Source-Contrastive and Language-Contrastive Decoding](https://md.research.elamur.ai/free/en/papers/sennrich-2024-mitigating-hallucinations-off-target-machine/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Rico Sennrich, Jannis Vamvas, Alireza Mohammadshahi*2024 · 47 citations*
318. [**Towards Mitigating Hallucination in Large Language Models via Self-Reflection arXiv:2310.06271**Ziwei Ji, Tiezheng Yu, Yan Xu, et al.*2023 · 47 citations*](https://md.research.elamur.ai/free/en/papers/ji-2023-towards-mitigating-hallucination-large-language/)
319. [**Language models scale reliably with over-training and on downstream tasks arXiv:2403.08540**Samir Yitzhak Gadre, Georgios Smyrnis, Vaishaal Shankar, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/gadre-2024-language-models-scale-reliably-over/)
320. [**Understanding Catastrophic Forgetting in Language Models via Implicit Inference arXiv:2309.10105**Suhas Kotha, Jacob Mitchell Springer, Aditi Raghunathan*2023 · 45 citations*](https://md.research.elamur.ai/free/en/papers/kotha-2023-understanding-catastrophic-forgetting-language-models/)
321. [**NVLM: Open Frontier-Class Multimodal LLMs arXiv:2409.11402**Wenliang Dai, Nayeon Lee, Boxin Wang, et al.*2024 · 44 citations*](https://md.research.elamur.ai/free/en/papers/dai-2024-nvlm-open-frontier-class-multimodal/)
322. [**Reka Core, Flash, and Edge: A Series of Powerful Multimodal Language Models arXiv:2404.12387**Reka Team: Aitor Ormazabal, Che Zheng, Cyprien de Masson d'Autume, et al.*2024 · 42 citations*](https://md.research.elamur.ai/free/en/papers/ormazabal-2024-reka-core-flash-edge-series/)
323. [**When does In-context Learning Fall Short and Why? A Study on Specification-Heavy Tasks arXiv:2311.08993**Hao Peng, Xiaozhi Wang, Jianhui Chen, et al.*2023 · 42 citations*](https://md.research.elamur.ai/free/en/papers/peng-2023-context-learning-fall-short-why/)
324. [**Transcending Scaling Laws with 0.1% Extra Compute arXiv:2210.11399**Yi Tay, Jason Wei, Hyung Won Chung, et al.*2022 · 42 citations*](https://md.research.elamur.ai/free/en/papers/tay-2022-transcending-scaling-laws-0-1/)
325. [**SALMON: Self-Alignment with Instructable Reward Models arXiv:2310.05910**Zhiqing Sun, Yikang Shen, Hongxin Zhang, et al.*2023 · 41 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-salmon-self-alignment-instructable-reward/)
326. **[FollowIR: Evaluating and Teaching Information Retrieval Models to Follow Instructions](https://md.research.elamur.ai/free/en/papers/weller-2025-followir-evaluating-teaching-information-retrieval/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Orion Weller, Benjamin Chang, Sean MacAvaney, et al.*2025 · 40 citations*
327. [**Conifer: Improving Complex Constrained Instruction-Following Ability of Large Language Models arXiv:2404.02823**Haoran Sun, Lixin Liu, Junjie Li, et al.*2024 · 40 citations*](https://md.research.elamur.ai/free/en/papers/sun-2024-conifer-improving-complex-constrained-instruction/)
328. **[Personalized Pieces: Efficient Personalized Large Language Models through Collaborative Efforts](https://md.research.elamur.ai/free/en/papers/tan-2024-personalized-pieces-efficient-personalized-large/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhaoxuan Tan, Zheyuan Liu, Meng Jiang*2024 · 40 citations*
329. **[Learning to Edit: Aligning LLMs with Knowledge Editing](https://md.research.elamur.ai/free/en/papers/jiang-2024-learning-edit-aligning-llms-knowledge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuxin Jiang, Yufei Wang, Chuhan Wu, et al.*2024 · 39 citations*
330. **[Multi-LogiEval: Towards Evaluating Multi-Step Logical Reasoning Ability of Large Language Models](https://md.research.elamur.ai/free/en/papers/patel-2024-multi-logieval-evaluating-multi-step/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Nisarg Patel, Mohith Kulkarni, Mihir Parmar, et al.*2024 · 39 citations*
331. **[InstructMol: Multi-Modal Integration for Building a Versatile and Reliable Molecular Assistant in Drug Discovery](https://md.research.elamur.ai/free/en/papers/cao-2025-instructmol-multi-modal-integration-building/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**He Cao, Zijing Liu, Xingyu Lu, et al.*2025 · 38 citations*
332. **[JASMINE: Arabic GPT Models for Few-Shot Learning](https://md.research.elamur.ai/free/en/papers/nagoudi-2023-jasmine-arabic-gpt-models-few/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**El Moatez Billah Nagoudi, Muhammad Abdul-Mageed, AbdelRahim Elmadany, et al.*2023 · 38 citations*
333. **[Towards Effective Disambiguation for Machine Translation with Large Language Models](https://md.research.elamur.ai/free/en/papers/iyer-2023-effective-disambiguation-machine-translation-large/) [Conference on Machine Translation (WMT)](https://md.research.elamur.ai/free/en/venues/wmt/)**Vivek Iyer, Pinzhen Chen, Alexandra Birch*2023 · 38 citations*
334. **[Aligning Large Language Models with Human Preferences through Representation Engineering](https://md.research.elamur.ai/free/en/papers/liu-2024-aligning-large-language-models-human/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenhao Liu, Xiaohua Wang, Muling Wu, et al.*2024 · 37 citations*
335. [**Efficient Language Model Training through Cross-Lingual and Progressive Transfer Learning arXiv:2301.09626**Malte Ostendorff, Georg Rehm*2023 · 36 citations*](https://md.research.elamur.ai/free/en/papers/ostendorff-2023-efficient-language-model-training-through/)
336. [**Efficient Online Data Mixing For Language Model Pre-Training arXiv:2312.02406**Alon Albalak, Liangming Pan, Colin Raffel, et al.*2023 · 35 citations*](https://md.research.elamur.ai/free/en/papers/albalak-2023-efficient-online-data-mixing-language/)
337. [**EuroBERT: Scaling Multilingual Encoders for European Languages arXiv:2503.05500**Nicolas Boizard, Hippolyte Gisserot-Boukhlef, Duarte M. Alves, et al.*2025 · 34 citations*](https://md.research.elamur.ai/free/en/papers/boizard-2025-eurobert-scaling-multilingual-encoders-european/)
338. [**M3KE: A Massive Multi-Level Multi-Subject Knowledge Evaluation Benchmark for Chinese Large Language Models arXiv:2305.10263**Chuang Liu, Renren Jin, Yuqi Ren, et al.*2023 · 34 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-m3ke-massive-multi-level/)
339. **[Evaluating Language Models as Synthetic Data Generators](https://md.research.elamur.ai/free/en/papers/kim-2025-evaluating-language-models-as-synthetic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Seungone Kim, Juyoung Suk, Xiang Yue, et al.*2025 · 32 citations*
340. [**Augmented Large Language Models with Parametric Knowledge Guiding arXiv:2305.04757**Ziyang Luo, Can Xu, Pu Zhao, et al.*2023 · 32 citations*](https://md.research.elamur.ai/free/en/papers/luo-2023-augmented-large-language-models-parametric/)
341. [**Interpretable Unified Language Checking arXiv:2304.03728**Tianhua Zhang, Hongyin Luo, Yung-Sung Chuang, et al.*2023 · 32 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-interpretable-unified-language-checking/)
342. [**Step-Audio 2 Technical Report arXiv:2507.16632**Boyong Wu, Chao Yan, Chen Hu, et al.*2025 · 31 citations*](https://md.research.elamur.ai/free/en/papers/wu-2025-step-audio-2-technical/)
343. [**The Life Cycle of Knowledge in Big Language Models: A Survey arXiv:2303.07616 · Machine Intelligence Research. vol. 21, no. 2, pp. 217-238, 2024**Boxi Cao, Hongyu Lin, Xianpei Han, et al.*2023 · 31 citations*](https://md.research.elamur.ai/free/en/papers/cao-2023-life-cycle-knowledge-big-language/)
344. **[CFBench: A Comprehensive Constraints-Following Benchmark for LLMs](https://md.research.elamur.ai/free/en/papers/zhang-2025-cfbench-comprehensive-constraints-following-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tao Zhang, ChengLIn Zhu, Yanjun Shen, et al.*2025 · 30 citations*
345. **[CIDAR: Culturally Relevant Instruction Dataset For Arabic](https://md.research.elamur.ai/free/en/papers/alyafeai-2024-cidar-culturally-relevant-instruction-dataset/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zaid Alyafeai, Khalid Almubarak, Ahmed Ashraf, et al.*2024 · 30 citations*
346. [**Jamba-1.5: Hybrid Transformer-Mamba Models at Scale arXiv:2408.12570**Jamba Team: Barak Lenz, Alan Arazi, Amir Bergman, et al.*2024 · 30 citations*](https://md.research.elamur.ai/free/en/papers/lenz-2024-jamba-1-5-hybrid-transformer/)
347. **[Persona-DB: Efficient Large Language Model Personalization for Response Prediction with Collaborative Data Refinement](https://md.research.elamur.ai/free/en/papers/sun-2025-persona-db-efficient-large-language/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Chenkai Sun, Ke Yang, Revanth Gangi Reddy, et al.*2025 · 29 citations*
348. **[Mind the instructions: a holistic evaluation of consistency and interactions in prompt-based learning](https://md.research.elamur.ai/free/en/papers/weber-2023-mind-instructions-holistic-evaluation-consistency/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Lucas Weber, Elia Bruni, Dieuwke Hupkes*2023 · 29 citations*
349. [**One Law, Many Languages: Benchmarking Multilingual Legal Reasoning for Judicial Support arXiv:2306.09237**Ronja Stern, Vishvaksenan Rasiah, Veton Matoshi, et al.*2023 · 29 citations*](https://md.research.elamur.ai/free/en/papers/stern-2023-one-law-many-languages-benchmarking/)
350. **[PLUG: Leveraging Pivot Language in Cross-Lingual Instruction Tuning](https://md.research.elamur.ai/free/en/papers/zhang-2024-plug-leveraging-pivot-language-cross/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhihan Zhang, Dong-Ho Lee, Yuwei Fang, et al.*2024 · 28 citations*
351. **[Can Large Language Models Unlock Novel Scientific Research Ideas?](https://md.research.elamur.ai/free/en/papers/kumar-2025-can-large-language-models-unlock/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Sandeep Kumar, Tirthankar Ghosal, Vinayak Goyal, et al.*2025 · 27 citations*
352. **[SciRIFF: A Resource to Enhance Language Model Instruction-Following over Scientific Literature](https://md.research.elamur.ai/free/en/papers/wadden-2025-sciriff-resource-enhance-language-model/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**David Wadden, Kejian Shi, Jacob Morrison, et al.*2025 · 27 citations*
353. [**Reviewer2: Optimizing Review Generation Through Prompt Generation arXiv:2402.10886**Zhaolin Gao, Kiante Brantley, Thorsten Joachims*2024 · 27 citations*](https://md.research.elamur.ai/free/en/papers/gao-2024-reviewer2-optimizing-review-generation-through/)
354. **[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*
355. [**PlaSma: Making Small Language Models Better Procedural Knowledge Models for (Counterfactual) Planning arXiv:2305.19472**Faeze Brahman, Chandra Bhagavatula, Valentina Pyatkin, et al.*2023 · 25 citations*](https://md.research.elamur.ai/free/en/papers/brahman-2023-plasma-making-small-language-models/)
356. [**From Zero to Hero: Examining the Power of Symbolic Tasks in Instruction Tuning arXiv:2304.07995**Qian Liu, Fan Zhou, Zhengbao Jiang, et al.*2023 · 24 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-zero-hero-examining-power-symbolic/)
357. **[Middle-Layer Representation Alignment for Cross-Lingual Transfer in Fine-Tuned LLMs](https://md.research.elamur.ai/free/en/papers/liu-2025-middle-layer-representation-alignment-cross/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Danni Liu, Jan Niehues*2025 · 23 citations*
358. [**RWKV-7 "Goose" with Expressive Dynamic State Evolution arXiv:2503.14456**Bo Peng, Ruichong Zhang, Daniel Goldstein, et al.*2025 · 23 citations*](https://md.research.elamur.ai/free/en/papers/peng-2025-rwkv-7-goose-expressive-dynamic/)
359. **[DDK: Distilling Domain Knowledge for Efficient Large Language Models](https://md.research.elamur.ai/free/en/papers/liu-2024-ddk-distilling-domain-knowledge-efficient/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jiaheng Liu, Chenchen Zhang, Jinyang Guo, et al.*2024 · 23 citations*
360. **[How Likely Do LLMs with CoT Mimic Human Reasoning?](https://md.research.elamur.ai/free/en/papers/bao-2025-how-likely-do-llms-cot/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Guangsheng Bao, Hongbo Zhang, Cunxiang Wang, et al.*2025 · 22 citations*
361. [**InstructAlign: High-and-Low Resource Language Alignment via Continual Crosslingual Instruction Tuning arXiv:2305.13627**Samuel Cahyawijaya, Holy Lovenia, Tiezheng Yu, et al.*2023 · 22 citations*](https://md.research.elamur.ai/free/en/papers/cahyawijaya-2023-instructalign-high-low-resource-language/)
362. [**Source-Aware Training Enables Knowledge Attribution in Language Models arXiv:2404.01019**Muhammad Khalifa, David Wadden, Emma Strubell, et al.*2024 · 21 citations*](https://md.research.elamur.ai/free/en/papers/khalifa-2024-source-aware-training-enables-knowledge/)
363. **[Teaching Small Language Models Reasoning through Counterfactual Distillation](https://md.research.elamur.ai/free/en/papers/feng-2024-teaching-small-language-models-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tao Feng, Yicheng Li, Chenglin Li, et al.*2024 · 21 citations*
364. **[CRAFT Your Dataset: Task-Specific Synthetic Dataset Generation Through Corpus Retrieval and Augmentation](https://md.research.elamur.ai/free/en/papers/ziegler-2025-craft-your-dataset-task-specific/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ingo Ziegler, Abdullatif Köksal, Desmond Elliott, et al.*2025 · 20 citations*
365. [**DADA: Dialect Adaptation via Dynamic Aggregation of Linguistic Rules**Yanchen Liu, William Held, Diyi Yang*2023 · 20 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-dada-dialect-adaptation-dynamic-aggregation/)
366. **[Code to Think, Think to Code: A Survey on Code-Enhanced Reasoning and Reasoning-Driven Code Intelligence in LLMs](https://md.research.elamur.ai/free/en/papers/yang-2025-code-think-think-code-survey/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Dayu Yang, Tianyang Liu, Daoan Zhang, et al.*2025 · 19 citations*
367. **[ConCISE: Confidence-guided Compression in Step-by-step Efficient Reasoning](https://md.research.elamur.ai/free/en/papers/qiao-2025-concise-confidence-guided-compression-step/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ziqing Qiao, Yongheng Deng, Jiali Zeng, et al.*2025 · 19 citations*
368. **[Can we obtain significant success in RST discourse parsing by using Large Language Models?](https://md.research.elamur.ai/free/en/papers/maekawa-2024-can-we-obtain-significant-success/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Aru Maekawa, Tsutomu Hirao, Hidetaka Kamigaito, et al.*2024 · 19 citations*
369. [**In-Context Principle Learning from Mistakes arXiv:2402.05403**Tianjun Zhang, Aman Madaan, Luyu Gao, et al.*2024 · 19 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-context-principle-learning-mistakes/)
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371. [**Vibe-Eval: A hard evaluation suite for measuring progress of multimodal language models arXiv:2405.02287**Piotr Padlewski, Max Bain, Matthew Henderson, et al.*2024 · 19 citations*](https://md.research.elamur.ai/free/en/papers/padlewski-2024-vibe-eval-hard-evaluation-suite/)
372. [**Quality-Diversity through AI Feedback arXiv:2310.13032**Herbie Bradley, Andrew Dai, Hannah Teufel, et al.*2023 · 19 citations*](https://md.research.elamur.ai/free/en/papers/bradley-2023-quality-diversity-through-ai-feedback/)
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400. [**Multilingual Arbitrage: Optimizing Data Pools to Accelerate Multilingual Progress arXiv:2408.14960**Ayomide Odumakinde, Daniel D'souza, Pat Verga, et al.*2024 · 12 citations*](https://md.research.elamur.ai/free/en/papers/odumakinde-2024-multilingual-arbitrage-optimizing-data-pools/)

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