---
title: "Who cites Diogo Almeida — page 5"
description: "13,639 papers of the Elamur Research library cite the works of Diogo Almeida, found in their bibliographies · page 5 of 8 · 401–500; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/diogo-almeida/cited-by/page/5/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/diogo-almeida/cited-by/page/5/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Diogo Almeida](https://md.research.elamur.ai/free/en/authors/diogo-almeida/) / [cited by](https://md.research.elamur.ai/free/en/authors/diogo-almeida/cited-by/) / page 5

# Who cites Diogo Almeida

16,073 citations of their works from 13,639 papers of our library (of the 140,884 whose bibliographies we read) · 799 with a page here, the most cited first · page 5 of 8 · 401–500 · [← Diogo Almeida](https://md.research.elamur.ai/free/en/authors/diogo-almeida/)

[← prev](https://md.research.elamur.ai/free/en/authors/diogo-almeida/cited-by/page/4/) [1](https://md.research.elamur.ai/free/en/authors/diogo-almeida/cited-by/) … [4](https://md.research.elamur.ai/free/en/authors/diogo-almeida/cited-by/page/4/) **5** [6](https://md.research.elamur.ai/free/en/authors/diogo-almeida/cited-by/page/6/) [7](https://md.research.elamur.ai/free/en/authors/diogo-almeida/cited-by/page/7/) [8](https://md.research.elamur.ai/free/en/authors/diogo-almeida/cited-by/page/8/) [next →](https://md.research.elamur.ai/free/en/authors/diogo-almeida/cited-by/page/6/)

401. [**Quark: Controllable Text Generation with Reinforced Unlearning**Ximing Lu, Sean Welleck, Jack Hessel, et al.*2022 · 164 citations*](https://md.research.elamur.ai/free/en/papers/lu-2022-quark-controllable-text-generation-reinforced/)
402. [**BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions**Terry Yue Zhuo, Minh Chien Vu, Jenny Chim, et al.*2024 · 163 citations*](https://md.research.elamur.ai/free/en/papers/zhuo-2024-bigcodebench-benchmarking-code-generation-diverse/)
403. [**CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer**Zhuoyi Yang, Jiayan Teng, Wendi Zheng, et al.*2024 · 163 citations*](https://md.research.elamur.ai/free/en/papers/yang-2024-cogvideox-text-video-diffusion/)
404. [**Improve Mathematical Reasoning in Language Models by Automated Process Supervision**Liangchen Luo, Yinxiao Liu, Rosanne Liu, et al.*2024 · 163 citations*](https://md.research.elamur.ai/free/en/papers/luo-2024-improve-mathematical-reasoning-language-models/)
405. [**Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision**Collin Burns, Pavel Izmailov, Jan Hendrik Kirchner, et al.*2023 · 163 citations*](https://md.research.elamur.ai/free/en/papers/burns-2023-weak-strong-generalization-eliciting-strong/)
406. [**Long-form factuality in large language models**Jerry Wei, Chengrun Yang, Xinying Song, et al.*2024 · 162 citations*](https://md.research.elamur.ai/free/en/papers/wei-2024-long-form-factuality-large-language/)
407. [**Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation**Yangsibo Huang, Samyak Gupta, Mengzhou Xia, et al.*2023 · 162 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-catastrophic-jailbreak-open-source-llms/)
408. [**GPTFUZZER: Red Teaming Large Language Models with Auto-Generated Jailbreak Prompts**Jiahao Yu, Xingwei Lin, Zheng Yu, et al.*2023 · 162 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-gptfuzzer-red-teaming-large-language/)
409. [**LooGLE: Can Long-Context Language Models Understand Long Contexts?**Jiaqi Li, Mengmeng Wang, Zilong Zheng, et al.*2023 · 162 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-loogle-long-context-language-models/)
410. [**Describe, Explain, Plan and Select: Interactive Planning with Large Language Models Enables Open-World Multi-Task Agents**Zihao Wang, Shaofei Cai, Guanzhou Chen, et al.*2023 · 161 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-describe-explain-plan-select-interactive/)
411. [**CultureLLM: Incorporating Cultural Differences into Large Language Models**Cheng Li, Mengzhou Chen, Jindong Wang, et al.*2024 · 160 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-culturellm-incorporating-cultural-differences-large/)
412. [**Scaling Synthetic Data Creation with 1,000,000,000 Personas**Tao Ge, Xin Chan, Xiaoyang Wang, et al.*2024 · 160 citations*](https://md.research.elamur.ai/free/en/papers/ge-2024-scaling-synthetic-data-creation-1/)
413. [**ChatGPT as a Factual Inconsistency Evaluator for Text Summarization**Zheheng Luo, Qianqian Xie, Sophia Ananiadou*2023 · 160 citations*](https://md.research.elamur.ai/free/en/papers/luo-2023-chatgpt-factual-inconsistency-evaluator-text/)
414. [**Orca 2: Teaching Small Language Models How to Reason**Arindam Mitra, Luciano Del Corro, Shweti Mahajan, et al.*2023 · 160 citations*](https://md.research.elamur.ai/free/en/papers/mitra-2023-orca-2-teaching-small-language/)
415. [**The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets**Samuel Marks, Max Tegmark*2023 · 160 citations*](https://md.research.elamur.ai/free/en/papers/marks-2023-geometry-truth-emergent-linear-structure/)
416. [**Reasoning with Language Model Prompting: A Survey**Shuofei Qiao, Yixin Ou, Ningyu Zhang, et al.*2022 · 160 citations*](https://md.research.elamur.ai/free/en/papers/qiao-2022-reasoning-language-model-prompting-survey/)
417. [**InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency**Weiyun Wang, Zhangwei Gao, Lixin Gu, et al.*2025 · 159 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-internvl3-5-advancing-open/)
418. [**MiniCheck: Efficient Fact-Checking of LLMs on Grounding Documents**Liyan Tang, Philippe Laban, Greg Durrett*2024 · 159 citations*](https://md.research.elamur.ai/free/en/papers/tang-2024-minicheck-efficient-fact-checking-llms/)
419. [**Omni-MATH: A Universal Olympiad Level Mathematic Benchmark For Large Language Models**Bofei Gao, Feifan Song, Zhe Yang, et al.*2024 · 159 citations*](https://md.research.elamur.ai/free/en/papers/gao-2024-omni-math-universal-olympiad-level/)
420. [**AgentTuning: Enabling Generalized Agent Abilities for LLMs**Aohan Zeng, Mingdao Liu, Rui Lu, et al.*2023 · 158 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2023-agenttuning-enabling-generalized-agent/)
421. [**FacTool: Factuality Detection in Generative AI — A Tool Augmented Framework for Multi-Task and Multi-Domain Scenarios**I-Chun Chern, Steffi Chern, Shiqi Chen, et al.*2023 · 158 citations*](https://md.research.elamur.ai/free/en/papers/chern-2023-factool-factuality-detection-generative-ai/)
422. [**GPT-4 Is Too Smart To Be Safe: Stealthy Chat with LLMs via Cipher**Youliang Yuan, Wenxiang Jiao, Wenxuan Wang, et al.*2023 · 158 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2023-gpt-4-too-smart-safe/)
423. [**From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning**Ming Li, Yong Zhang, Zhitao Li, et al.*2023 · 157 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-quantity-quality-boosting-llm-performance/)
424. [**SmoothLLM: Defending Large Language Models Against Jailbreaking Attacks**Alexander Robey, Eric Wong, Hamed Hassani, et al.*2023 · 157 citations*](https://md.research.elamur.ai/free/en/papers/robey-2023-smoothllm-defending-large-language-models/)
425. [**The Linear Representation Hypothesis and the Geometry of Large Language Models**Kiho Park, Yo Joong Choe, Victor Veitch*2023 · 157 citations*](https://md.research.elamur.ai/free/en/papers/park-2023-linear-representation-hypothesis-geometry-large/)
426. [**DataComp-LM: In search of the next generation of training sets for language models**Jeffrey Li, Alex Fang, Georgios Smyrnis, et al.*2024 · 156 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-datacomp-lm-search-next-generation/)
427. [**VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks**Jing Yu Koh, Robert Lo, Lawrence Jang, et al.*2024 · 156 citations*](https://md.research.elamur.ai/free/en/papers/koh-2024-visualwebarena-evaluating-multimodal-agents-realistic/)
428. [**Large Language Models Effectively Leverage Document-level Context for Literary Translation, but Critical Errors Persist**Marzena Karpinska, Mohit Iyyer*2023 · 156 citations*](https://md.research.elamur.ai/free/en/papers/karpinska-2023-large-language-models-effectively-leverage/)
429. [**The Devil Is in the Errors: Leveraging Large Language Models for Fine-grained Machine Translation Evaluation**Patrick Fernandes, Daniel Deutsch, Mara Finkelstein, et al.*2023 · 156 citations*](https://md.research.elamur.ai/free/en/papers/fernandes-2023-devil-is-errors-leveraging-large/)
430. [**The Lessons of Developing Process Reward Models in Mathematical Reasoning**Zhenru Zhang, Chujie Zheng, Yangzhen Wu, et al.*2025 · 155 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-lessons-developing-process-reward-models/)
431. [**HunyuanVideo: A Systematic Framework For Large Video Generative Models**Weijie Kong, Qi Tian, Zijian Zhang, et al.*2024 · 155 citations*](https://md.research.elamur.ai/free/en/papers/kong-2024-hunyuanvideo-systematic-framework-large/)
432. [**WildGuard: Open One-Stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs**Seungju Han, Kavel Rao, Allyson Ettinger, et al.*2024 · 155 citations*](https://md.research.elamur.ai/free/en/papers/han-2024-wildguard-open-one-stop-moderation/)
433. [**ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMs**Justin Chen, Swarnadeep Saha, Mohit Bansal*2024 · 154 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-reconcile-round-table-conference-improves/)
434. [**TheoremQA: A Theorem-driven Question Answering Dataset**Wenhu Chen, Ming Yin, Max Ku, et al.*2023 · 154 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-theoremqa-theorem-driven-question-answering/)
435. [**Leveraging Large Language Models for Multiple Choice Question Answering**Joshua Robinson, Christopher Michael Rytting, David Wingate*2022 · 154 citations*](https://md.research.elamur.ai/free/en/papers/robinson-2022-leveraging-large-language-models-multiple/)
436. [**SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training**Tianzhe Chu, Yuexiang Zhai, Jihan Yang, et al.*2025 · 151 citations*](https://md.research.elamur.ai/free/en/papers/chu-2025-sft-memorizes-rl-generalizes-comparative/)
437. [**Language-Specific Neurons: The Key to Multilingual Capabilities in Large Language Models**Tianyi Tang, Wenyang Luo, Haoyang Huang, et al.*2024 · 151 citations*](https://md.research.elamur.ai/free/en/papers/tang-2024-language-specific-neurons-key-multilingual/)
438. [**PyramidKV: Dynamic KV Cache Compression based on Pyramidal Information Funneling**Zefan Cai, Yichi Zhang, Bofei Gao, et al.*2024 · 151 citations*](https://md.research.elamur.ai/free/en/papers/cai-2024-pyramidkv-dynamic-kv-cache-compression/)
439. [**ChatGPT MT: Competitive for High- (but Not Low-) Resource Languages**Nathaniel Robinson, Perez Ogayo, David R. Mortensen, et al.*2023 · 151 citations*](https://md.research.elamur.ai/free/en/papers/robinson-2023-chatgpt-mt-competitive-high-but/)
440. [**The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models**Junyi Li, Jie Chen, Ruiyang Ren, et al.*2024 · 150 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-dawn-after-dark-empirical-study/)
441. [**AnnoLLM: Making Large Language Models to Be Better Crowdsourced Annotators**Xingwei He, Zhenghao Lin, Yeyun Gong, et al.*2023 · 150 citations*](https://md.research.elamur.ai/free/en/papers/he-2023-annollm-making-large-language-models/)
442. [**Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigation**Niels Mundler, Jingxuan He, Slobodan Jenko, et al.*2023 · 150 citations*](https://md.research.elamur.ai/free/en/papers/mundler-2023-self-contradictory-hallucinations-large-language/)
443. [**Chain-of-Note: Enhancing Robustness in Retrieval-Augmented Language Models**Wenhao Yu, Hongming Zhang, Xiaoman Pan, et al.*2024 · 149 citations*](https://md.research.elamur.ai/free/en/papers/yu-2024-chain-note-enhancing-robustness-retrieval/)
444. [**Language Model Tokenizers Introduce Unfairness Between Languages**Aleksandar Petrov, Emanuele La Malfa, Philip H. S. Torr, et al.*2023 · 149 citations*](https://md.research.elamur.ai/free/en/papers/petrov-2023-language-model-tokenizers-introduce-unfairness/)
445. [**ProsocialDialog: A Prosocial Backbone for Conversational Agents**Hyunwoo Kim, Youngjae Yu, Liwei Jiang, et al.*2022 · 149 citations*](https://md.research.elamur.ai/free/en/papers/kim-2022-prosocialdialog-prosocial-backbone-conversational-agents/)
446. [**SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models**Xiaoxuan Wang, Ziniu Hu, Pan Lu, et al.*2023 · 148 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-scibench-evaluating-college-level-scientific/)
447. [**Process Reinforcement through Implicit Rewards**Ganqu Cui, Lifan Yuan, Zefan Wang, et al.*2025 · 147 citations*](https://md.research.elamur.ai/free/en/papers/cui-2025-process-reinforcement-through-implicit-rewards/)
448. [**BLEnD: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and Languages**Junho Myung, Nayeon Lee, Yi Zhou, et al.*2024 · 147 citations*](https://md.research.elamur.ai/free/en/papers/myung-2024-blend-benchmark-llms-everyday-knowledge/)
449. [**rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking**Xinyu Guan, Li Lyna Zhang, Yifei Liu, et al.*2025 · 146 citations*](https://md.research.elamur.ai/free/en/papers/guan-2025-rstar-math-small-llms-can/)
450. [**Fast-DetectGPT: Efficient Zero-Shot Detection of Machine-Generated Text via Conditional Probability Curvature**Guangsheng Bao, Yanbin Zhao, Zhiyang Teng, et al.*2023 · 146 citations*](https://md.research.elamur.ai/free/en/papers/bao-2023-fast-detectgpt-efficient-zero-shot/)
451. [**How Abilities in Large Language Models are Affected by Supervised Fine-tuning Data Composition**Guanting Dong, Hongyi Yuan, Keming Lu, et al.*2024 · 145 citations*](https://md.research.elamur.ai/free/en/papers/dong-2024-how-abilities-large-language-models/)
452. [**Unlocking Efficiency in Large Language Model Inference: A Comprehensive Survey of Speculative Decoding**Heming Xia, Zhe Yang, Qingxiu Dong, et al.*2024 · 145 citations*](https://md.research.elamur.ai/free/en/papers/xia-2024-unlocking-efficiency-large-language-model/)
453. [**Fact-Checking Complex Claims with Program-Guided Reasoning**Liangming Pan, Xiaobao Wu, Xinyuan Lu, et al.*2023 · 145 citations*](https://md.research.elamur.ai/free/en/papers/pan-2023-fact-checking-complex-claims-program/)
454. [**RA-DIT: Retrieval-Augmented Dual Instruction Tuning**Xi Victoria Lin, Xilun Chen, Mingda Chen, et al.*2023 · 145 citations*](https://md.research.elamur.ai/free/en/papers/lin-2023-ra-dit-retrieval-augmented-dual/)
455. [**Self-Evaluation Guided Beam Search for Reasoning**Yuxi Xie, Kenji Kawaguchi, Yiran Zhao, et al.*2023 · 145 citations*](https://md.research.elamur.ai/free/en/papers/xie-2023-self-evaluation-guided-beam-search/)
456. [**Iterative Reasoning Preference Optimization**Richard Yuanzhe Pang, Weizhe Yuan, Kyunghyun Cho, et al.*2024 · 144 citations*](https://md.research.elamur.ai/free/en/papers/pang-2024-iterative-reasoning-preference-optimization/)
457. [**Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing**Zhangchen Xu, Fengqing Jiang, Luyao Niu, et al.*2024 · 144 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-magpie-alignment-data-synthesis-scratch/)
458. [**Unified Demonstration Retriever for In-Context Learning**Xiaonan Li, Kai Lv, Hang Yan, et al.*2023 · 144 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-unified-demonstration-retriever-context-learning/)
459. [**Verify-and-Edit: A Knowledge-Enhanced Chain-of-Thought Framework**Ruochen Zhao, Xingxuan Li, Shafiq Joty, et al.*2023 · 144 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-verify-edit-knowledge-enhanced-chain/)
460. [**Is GPT-3 a Good Data Annotator?**Bosheng Ding, Chengwei Qin, Linlin Liu, et al.*2022 · 144 citations*](https://md.research.elamur.ai/free/en/papers/ding-2022-gpt-3-good-data-annotator/)
461. [**Generative Verifiers: Reward Modeling as Next-Token Prediction**Lunjun Zhang, Arian Hosseini, Hritik Bansal, et al.*2024 · 143 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-generative-verifiers-reward-modeling-as/)
462. [**MiniLLM: On-Policy Distillation of Large Language Models**Yuxian Gu, Li Dong, Furu Wei, et al.*2023 · 143 citations*](https://md.research.elamur.ai/free/en/papers/gu-2023-minillm-policy-distillation-large-language/)
463. [**Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning**Shenzhi Wang, Le Yu, Chang Gao, et al.*2025 · 142 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-80-20-rule-high-entropy/)
464. [**Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Experts**Haoxiang Wang, Wei Xiong, Tengyang Xie, et al.*2024 · 142 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-interpretable-preferences-multi-objective-reward/)
465. [**Justice or Prejudice? Quantifying Biases in LLM-as-a-Judge**Jiayi Ye, Yanbo Wang, Yue Huang, et al.*2024 · 142 citations*](https://md.research.elamur.ai/free/en/papers/ye-2024-justice-prejudice-quantifying-biases-llm/)
466. [**PMC-LLaMA: Towards Building Open-source Language Models for Medicine**Chaoyi Wu, Weixiong Lin, Xiaoman Zhang, et al.*2023 · 142 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-pmc-llama-towards-building-open/)
467. [**ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool Embeddings**Shibo Hao, Tianyang Liu, Zhen Wang, et al.*2023 · 142 citations*](https://md.research.elamur.ai/free/en/papers/hao-2023-toolkengpt-augmenting-frozen-language-models/)
468. [**JudgeLM: Fine-tuned Large Language Models are Scalable Judges**Lianghui Zhu, Xinggang Wang, Xinlong Wang*2023 · 141 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2023-judgelm-fine-tuned-large-language/)
469. [**A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation**Neeraj Varshney; Wenlin Yao; Hongming Zhang; Jianshu Chen;, Dong Yu*2023 · 139 citations*](https://md.research.elamur.ai/free/en/papers/varshney-2023-stitch-time-saves-nine-detecting/)
470. [**Diverse Demonstrations Improve In-context Compositional Generalization**Itay Levy, Ben Bogin, Jonathan Berant*2023 · 139 citations*](https://md.research.elamur.ai/free/en/papers/levy-2023-diverse-demonstrations-improve-context-compositional/)
471. [**The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learning**Bill Yuchen Lin, Abhilasha Ravichander, Ximing Lu, et al.*2023 · 139 citations*](https://md.research.elamur.ai/free/en/papers/lin-2023-unlocking-spell-base-llms-rethinking/)
472. [**Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration**Zhenhailong Wang, Shaoguang Mao, Wenshan Wu, et al.*2023 · 139 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-unleashing-emergent-cognitive-synergy-large/)
473. [**LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens**Yiran Ding, Li Lyna Zhang, Chengruidong Zhang, et al.*2024 · 138 citations*](https://md.research.elamur.ai/free/en/papers/ding-2024-longrope-extending-llm-context/)
474. [**DeepInception: Hypnotize Large Language Model to Be Jailbreaker**Xuan Li, Zhanke Zhou, Jianing Zhu, et al.*2023 · 138 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-deepinception-hypnotize-large-language-model/)
475. [**Investigating Data Contamination in Modern Benchmarks for Large Language Models**Chunyuan Deng, Yilun Zhao, Xiangru Tang, et al.*2024 · 137 citations*](https://md.research.elamur.ai/free/en/papers/deng-2024-investigating-data-contamination-modern-benchmarks/)
476. [**MLAgentBench: Evaluating Language Agents on Machine Learning Experimentation**Qian Huang, Jian Vora, Percy Liang, et al.*2023 · 137 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-mlagentbench-evaluating-language-agents/)
477. [**Efficient Training of Language Models to Fill in the Middle**Mohammad Bavarian, Heewoo Jun, Nikolas Tezak, et al.*2022 · 137 citations*](https://md.research.elamur.ai/free/en/papers/bavarian-2022-efficient-training-language-models-fill/)
478. [**Agent Laboratory: Using LLM Agents as Research Assistants**Samuel Schmidgall, Yusheng Su, Ze Wang, et al.*2025 · 136 citations*](https://md.research.elamur.ai/free/en/papers/schmidgall-2025-agent-laboratory-using-llm/)
479. [**A fine-grained comparison of pragmatic language understanding in humans and language models**Jennifer Hu, Sammy Floyd, Olessia Jouravlev, et al.*2023 · 136 citations*](https://md.research.elamur.ai/free/en/papers/hu-2023-fine-grained-comparison-pragmatic-language/)
480. [**Detecting Language Model Attacks with Perplexity**Gabriel Alon, Michael Kamfonas*2023 · 136 citations*](https://md.research.elamur.ai/free/en/papers/alon-2023-detecting-language-model-attacks-perplexity/)
481. [**MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback**Xingyao Wang, Zihan Wang, Jiateng Liu, et al.*2023 · 136 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-mint-evaluating-llms-multi-turn/)
482. [**mPLUG-Owl2: Revolutionizing Multi-modal Large Language Model with Modality Collaboration**Qinghao Ye, Haiyang Xu, Jiabo Ye, et al.*2023 · 136 citations*](https://md.research.elamur.ai/free/en/papers/ye-2023-mplug-owl2-revolutionizing-multi-modal/)
483. [**A Roadmap to Pluralistic Alignment**Taylor Sorensen, Jared Moore, Jillian Fisher, et al.*2024 · 135 citations*](https://md.research.elamur.ai/free/en/papers/sorensen-2024-roadmap-pluralistic-alignment/)
484. [**Error Analysis Prompting Enables Human-Like Translation Evaluation in Large Language Models**Qingyu Lu, Baopu Qiu, Liang Ding, et al.*2024 · 135 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-error-analysis-prompting-enables-human/)
485. [**Token-Budget-Aware LLM Reasoning**Tingxu Han, Zhenting Wang, Chunrong Fang, et al.*2024 · 135 citations*](https://md.research.elamur.ai/free/en/papers/han-2024-token-budget-aware-llm-reasoning/)
486. [**Scaling up CometKiwi: Unbabel-IST 2023 Submission for the Quality Estimation Shared Task**Ricardo Rei, Nuno M. Guerreiro, José Pombal, et al.*2023 · 135 citations*](https://md.research.elamur.ai/free/en/papers/rei-2023-scaling-up-cometkiwi-unbabel-ist/)
487. [**SLiC-HF: Sequence Likelihood Calibration with Human Feedback**Yao Zhao, Rishabh Joshi, Tianqi Liu, et al.*2023 · 135 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-slic-hf-sequence-likelihood-calibration/)
488. [**Political Compass or Spinning Arrow? Towards More Meaningful Evaluations for Values and Opinions in Large Language Models**Paul Röttger, Valentin Hofmann, Valentina Pyatkin, et al.*2024 · 134 citations*](https://md.research.elamur.ai/free/en/papers/rottger-2024-political-compass-or-spinning-arrow/)
489. [**Replacing Judges with Juries: Evaluating LLM Generations with a Panel of Diverse Models**Pat Verga, Sebastian Hofstatter, Sophia Althammer, et al.*2024 · 134 citations*](https://md.research.elamur.ai/free/en/papers/verga-2024-replacing-judges-juries-evaluating-llm/)
490. [**Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models**Avi Singh, John D. Co-Reyes, Rishabh Agarwal, et al.*2023 · 134 citations*](https://md.research.elamur.ai/free/en/papers/singh-2023-human-data-scaling-self-training/)
491. [**Few-Shot Self-Rationalization with Natural Language Prompts**Ana Marasovic, Iz Beltagy, Doug Downey, et al.*2022 · 134 citations*](https://md.research.elamur.ai/free/en/papers/marasovic-2022-few-shot-self-rationalization-natural/)
492. [**InFoBench: Evaluating Instruction Following Ability in Large Language Models**Yiwei Qin, Kaiqiang Song, Yebowen Hu, et al.*2024 · 133 citations*](https://md.research.elamur.ai/free/en/papers/qin-2024-infobench-evaluating-instruction-following-ability/)
493. [**To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning**Zayne Sprague, Fangcong Yin, Juan Diego Rodriguez, et al.*2024 · 133 citations*](https://md.research.elamur.ai/free/en/papers/sprague-2024-cot-cot-chain-thought-helps/)
494. [**Prompting is not a substitute for probability measurements in large language models**Jennifer Hu, Roger Levy*2023 · 133 citations*](https://md.research.elamur.ai/free/en/papers/hu-2023-prompting-is-not-substitute-probability/)
495. [**Long-context LLMs Struggle with Long In-context Learning**Tianle Li, Ge Zhang, Quy Duc Do, et al.*2024 · 132 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-long-context-llms-struggle-long/)
496. [**OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF Framework**Jian Hu, Xibin Wu, Wei Shen, et al.*2024 · 132 citations*](https://md.research.elamur.ai/free/en/papers/hu-2024-openrlhf-easy-use-scalable/)
497. [**EAGLE-2: Faster Inference of Language Models with Dynamic Draft Trees**Yuhui Li, Fangyun Wei, Chao Zhang, et al.*2024 · 131 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-eagle-2-faster-inference-language/)
498. [**ReFT: Reasoning with Reinforced Fine-Tuning**Luong Trung, Xinbo Zhang, Zhanming Jie, et al.*2024 · 131 citations*](https://md.research.elamur.ai/free/en/papers/trung-2024-reft-reasoning-reinforced-fine-tuning/)
499. [**Self-Alignment with Instruction Backtranslation**Xian Li, Ping Yu, Chunting Zhou, et al.*2023 · 131 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-self-alignment-instruction-backtranslation/)
500. [**Task-aware Retrieval with Instructions**Akari Asai, Timo Schick, Patrick Lewis, et al.*2023 · 131 citations*](https://md.research.elamur.ai/free/en/papers/asai-2023-task-aware-retrieval-instructions/)

[← prev](https://md.research.elamur.ai/free/en/authors/diogo-almeida/cited-by/page/4/) [1](https://md.research.elamur.ai/free/en/authors/diogo-almeida/cited-by/) … [4](https://md.research.elamur.ai/free/en/authors/diogo-almeida/cited-by/page/4/) **5** [6](https://md.research.elamur.ai/free/en/authors/diogo-almeida/cited-by/page/6/) [7](https://md.research.elamur.ai/free/en/authors/diogo-almeida/cited-by/page/7/) [8](https://md.research.elamur.ai/free/en/authors/diogo-almeida/cited-by/page/8/) [next →](https://md.research.elamur.ai/free/en/authors/diogo-almeida/cited-by/page/6/)

- [← back to](https://md.research.elamur.ai/free/en/authors/diogo-almeida/) — Diogo Almeida
