--- title: "Papers of 2023 — page 6" description: "Papers of 2023: 769 papers of the Elamur Research library — what each work is about in our own words, its ideas, references and who cites it." canonical: "https://research.elamur.ai/free/en/papers/2023/page/6/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/2023/page/6/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / 2023 # Papers of 2023 — page 6 769 papers · [all years](https://md.research.elamur.ai/free/en/papers/) [← prev](https://md.research.elamur.ai/free/en/papers/2023/page/5/) [1](https://md.research.elamur.ai/free/en/papers/2023/) … [5](https://md.research.elamur.ai/free/en/papers/2023/page/5/) **6** [7](https://md.research.elamur.ai/free/en/papers/2023/page/7/) [8](https://md.research.elamur.ai/free/en/papers/2023/page/8/) [next →](https://md.research.elamur.ai/free/en/papers/2023/page/7/) - [Orca 2: Teaching Small Language Models How to Reason](https://md.research.elamur.ai/free/en/papers/mitra-2023-orca-2-teaching-small-language/) — Arindam Mitra, Luciano Del Corro, Shweti Mahajan, et al. · arXiv:2311.11045 - [Orca: Progressive Learning from Complex Explanation Traces of GPT-4](https://md.research.elamur.ai/free/en/papers/mukherjee-2023-orca-progressive-learning-complex-explanation/) — Subhabrata Mukherjee, Arindam Mitra, Ganesh Jawahar, et al. · arXiv:2306.02707 - [OSN-MDAD: Machine Translation Dataset for Arabic Multi-Dialectal Conversations on Online Social Media](https://md.research.elamur.ai/free/en/papers/alzamzami-2023-osn-mdad-machine-translation-dataset/) — Fatimah Alzamzami, Abdulmotaleb El Saddik · arXiv:2309.12137 - [Otter: A Multi-Modal Model with In-Context Instruction Tuning](https://md.research.elamur.ai/free/en/papers/li-2023-otter-multi-modal-model-context/) — Bo Li, Yuanhan Zhang, Liangyu Chen, et al. · arXiv:2305.03726 - [Overview of PragTag-2023: Low-Resource Multi-Domain Pragmatic Tagging of Peer Reviews](https://md.research.elamur.ai/free/en/papers/dycke-2023-overview-pragtag-2023-low-resource/) — Nils Dycke, Ilia Kuznetsov, Iryna Gurevych · Proceedings of the 10th Workshop on Argument… - [PaLM 2 Technical Report](https://md.research.elamur.ai/free/en/papers/anil-2023-palm-2-technical-report/) — Rohan Anil, Andrew M. Dai, Orhan Firat, et al. · arXiv:2305.10403 - [PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization](https://md.research.elamur.ai/free/en/papers/wang-2023-pandalm-automatic-evaluation-benchmark-llm/) — Yidong Wang, Zhuohao Yu, Zhengran Zeng, et al. · arXiv:2306.05087 - [ParaAMR: A Large-Scale Syntactically Diverse Paraphrase Dataset by AMR Back-Translation](https://md.research.elamur.ai/free/en/papers/huang-2023-paraamr-large-scale-syntactically-diverse/) — Kuan-Hao Huang, Varun Iyer, I-Hung Hsu, et al. · Machine translation - [Parameter-efficient fine-tuning of large-scale pre-trained language models](https://md.research.elamur.ai/free/en/papers/ding-2023-parameter-efficient-fine-tuning-large/) — Ning Ding, Yujia Qin, Guang You Yang, et al. · Nature Machine Intelligence - [Paraphrasing evades detectors of AI-generated text, but retrieval is an effective defense](https://md.research.elamur.ai/free/en/papers/krishna-2023-paraphrasing-evades-detectors-ai-generated/) — Kalpesh Krishna, Yixiao Song, Marzena Karpinska, et al. · arXiv:2303.13408 - [Peer Teaching Method Integrated with Card Media: Its Implementation in Arabic Syntax Learning](https://md.research.elamur.ai/free/en/papers/rizal-2023-peer-teaching-method-integrated-card/) — Muhammad Rizal, Mohamad Zaka Al Farisi, Asep Sopian · Arabiyatuna: Jurnal Bahasa Arab 7 - [PEIT: Bridging the Modality Gap with Pre-trained Models for End-to-End Image Translation](https://md.research.elamur.ai/free/en/papers/zhu-2023-peit-bridging-modality-gap-pre/) — Shaolin Zhu, Shangjie Li, Yikun Lei, et al. · Proceedings of the 61st Annual Meeting of the… - [Personality Traits in Large Language Models](https://md.research.elamur.ai/free/en/papers/serapio-2023-garcia-personality-traits-large-language-models/) — Greg Serapio-Garcia, Mustafa Safdari, Clement Crepy, et al. · arXiv:2307.00184 - [Physics of Language Models: Part 3.1, Knowledge Storage and Extraction](https://md.research.elamur.ai/free/en/papers/allen-2023-zhu-physics-language-models-part-3/) — Zeyuan Allen-Zhu, Yuanzhi Li · arXiv:2309.14316 - [PMC-LLaMA: Towards Building Open-source Language Models for Medicine](https://md.research.elamur.ai/free/en/papers/wu-2023-pmc-llama-towards-building-open/) — Chaoyi Wu, Weixiong Lin, Xiaoman Zhang, et al. · arXiv:2304.14454 - [PragmatiCQA: A Dataset for Pragmatic Question Answering in Conversations](https://md.research.elamur.ai/free/en/papers/qi-2023-pragmaticqa-dataset-pragmatic-question-answering/) — Peng Qi, Nina Du, Christopher Manning, et al. · English - [Pragmatics in Language Grounding: Phenomena, Tasks, and Modeling Approaches](https://md.research.elamur.ai/free/en/papers/fried-2023-pragmatics-language-grounding-phenomena-tasks/) — Daniel Fried, Nicholas Tomlin, Jennifer Hu, et al. · Findings of the Association for Computational… - [Prediction of Arabic Legal Rulings using Large Language Models](https://md.research.elamur.ai/free/en/papers/ammar-2023-prediction-arabic-legal-rulings-using/) — Adel Ammar, Anis Koubaa, Bilel Benjdira, et al. · arXiv:2310.10260 - [Preference Ranking Optimization for Human Alignment](https://md.research.elamur.ai/free/en/papers/song-2023-preference-ranking-optimization-human-alignment/) — Feifan Song, Bowen Yu, Minghao Li, et al. · arXiv:2306.17492 - [Pretraining Language Models with Human Preferences](https://md.research.elamur.ai/free/en/papers/korbak-2023-pretraining-language-models-human-preferences/) — Tomasz Korbak, Kejian Shi, Angelica Chen, et al. · arXiv:2302.08582 - [PreWoMe: Exploiting Presuppositions as Working Memory for Long Form Question Answering](https://md.research.elamur.ai/free/en/papers/han-2023-prewome-exploiting-presuppositions-as-working/) — Wookje Han, Jinsol Park, Kyungjae Lee · English - [Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision](https://md.research.elamur.ai/free/en/papers/sun-2023-principle-driven-self-alignment-language/) — Zhiqing Sun, Yikang Shen, Qinhong Zhou, et al. · arXiv:2305.03047 - [Probing Pre-Trained Language Models for Cross-Cultural Differences in Values](https://md.research.elamur.ai/free/en/papers/arora-2023-probing-pre-trained-language-models/) — Arnav Arora, Lucie-aimée Kaffee, Isabelle Augenstein · Proceedings of the First Workshop on… - [Proceedings of the 2nd Edition of the Universal Dependencies Brazilian Festival](https://md.research.elamur.ai/free/en/papers/anon-2023-proceedings-2nd-edition-universal-dependencies/) — Research library - [Proceedings of the First International Workshop on Construction Grammars and NLP (CxGs+NLP, GURT/SyntaxFest 2023)](https://md.research.elamur.ai/free/en/papers/anon-2023-proceedings-first-international-workshop-construction/) — Research library - [Progress measures for grokking via mechanistic interpretability](https://md.research.elamur.ai/free/en/papers/nanda-2023-progress-measures-grokking-mechanistic-interpretability/) — Neel Nanda, Lawrence Chan, Tom Lieberum, et al. · arXiv:2301.05217 - [Prometheus: Inducing Fine-grained Evaluation Capability in Language Models](https://md.research.elamur.ai/free/en/papers/kim-2023-prometheus-inducing-fine-grained-evaluation/) — Seungone Kim, Jamin Shin, Yejin Cho, et al. · arXiv:2310.08491 - [Prompt Injection attack against LLM-integrated Applications](https://md.research.elamur.ai/free/en/papers/liu-2023-prompt-injection-attack-against-llm/) — Yi Liu; Gelei Deng; Yuekang Li; Kailong Wang; Zihao Wang; Xiaofeng Wang; Tianwei Zhang; Yepang Liu; Haoyu Wang; Yan Zheng; Leo Yu Zhang;, Yang Liu · arXiv:2306.05499 - [Prompt Tuning with Contradictory Intentions for Sarcasm Recognition](https://md.research.elamur.ai/free/en/papers/liu-2023-prompt-tuning-contradictory-intentions-sarcasm/) — Yiyi Liu, Ruqing Zhang, Yixing Fan, et al. · Proceedings of the 17th Conference of the… - [Prompt-based Logical Semantics Enhancement for Implicit Discourse Relation Recognition](https://md.research.elamur.ai/free/en/papers/wang-2023-prompt-based-logical-semantics-enhancement/) — Chenxu Wang, Ping Jian, Mu Huang · Proceedings of the 2023 Conference on Empirical… - [Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution](https://md.research.elamur.ai/free/en/papers/fernando-2023-promptbreeder-self-referential-self-improvement/) — Chrisantha Fernando, Dylan Banarse, Henryk Michalewski, et al. · arXiv:2309.16797 - [Prompting is not a substitute for probability measurements in large language models](https://md.research.elamur.ai/free/en/papers/hu-2023-prompting-is-not-substitute-probability/) — Jennifer Hu, Roger Levy · Proceedings of the 2023 Conference on Empirical… - [Prompting Large Language Model for Machine Translation: A Case Study](https://md.research.elamur.ai/free/en/papers/zhang-2023-prompting-large-language-model-machine/) — Biao Zhang, Barry Haddow, Alexandra Birch · arXiv:2301.07069 - [PromptRobust: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts](https://md.research.elamur.ai/free/en/papers/zhu-2023-promptrobust-towards-evaluating-robustness-large/) — Kaijie Zhu, Jindong Wang, Jiaheng Zhou, et al. · arXiv:2306.04528 - [ProofNet: Autoformalizing and Formally Proving Undergraduate-Level Mathematics](https://md.research.elamur.ai/free/en/papers/azerbayev-2023-proofnet-autoformalizing-formally-proving-undergraduate/) — Zhangir Azerbayev, Bartosz Piotrowski, Hailey Schoelkopf, et al. · arXiv:2302.12433 - [QA-KGNet: 一种语言模型驱动的知识图谱问答模型](https://md.research.elamur.ai/free/en/papers/qiao-2023-qa-kgnet-language/) — 乔少杰, 杨国平, 于泳, et al. · 软件学报 (Journal of Software) - [QUDeval: The Evaluation of Questions Under Discussion Discourse Parsing](https://md.research.elamur.ai/free/en/papers/wu-2023-qudeval-evaluation-questions-under-discussion/) — Yating Wu, Ritika Mangla, Greg Durrett, et al. · English - [Query Rewriting in Retrieval-Augmented Large Language Models](https://md.research.elamur.ai/free/en/papers/ma-2023-query-rewriting-retrieval-augmented-large/) — Xinbei Ma, Yeyun Gong, Pengcheng He, et al. · Proceedings of the 2023 Conference on Empirical… - [Query2doc: Query Expansion with Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2023-query2doc-query-expansion-large-language/) — Liang Wang, Nan Yang, Furu Wei · Proceedings of the 2023 Conference on Empirical… - [Quranic Conversations: Developing a Semantic Search tool for the Quran using Arabic NLP Techniques](https://md.research.elamur.ai/free/en/papers/shohoud-2023-quranic-conversations-developing-semantic-search/) — Yasser Shohoud, Maged Shoman, Sarah Abdelazim · arXiv:2311.05120 - [QVoice: Arabic Speech Pronunciation Learning Application](https://md.research.elamur.ai/free/en/papers/kheir-2023-qvoice-arabic-speech-pronunciation-learning/) — Yassine El Kheir, Fouad Khnaisser, Shammur Absar Chowdhury, et al. · arXiv:2305.07445 · InterSpeech 2023 - [Qwen Technical Report](https://md.research.elamur.ai/free/en/papers/bai-2023-qwen-technical-report/) — Jinze Bai, Shuai Bai, Yunfei Chu, et al. · arXiv:2309.16609 - [Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models](https://md.research.elamur.ai/free/en/papers/chu-2023-qwen-audio-advancing-universal/) — Yunfei Chu, Jin Xu, Xiaohuan Zhou, et al. · arXiv:2311.07919 - [Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond](https://md.research.elamur.ai/free/en/papers/bai-2023-qwen-vl-versatile-vision-language/) — Jinze Bai, Shuai Bai, Shusheng Yang, et al. · arXiv:2308.12966 - [RA-DIT: Retrieval-Augmented Dual Instruction Tuning](https://md.research.elamur.ai/free/en/papers/lin-2023-ra-dit-retrieval-augmented-dual/) — Xi Victoria Lin, Xilun Chen, Mingda Chen, et al. · arXiv:2310.01352 - [RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment](https://md.research.elamur.ai/free/en/papers/dong-2023-raft-reward-ranked-finetuning-generative/) — Hanze Dong, Wei Xiong, Deepanshu Goyal, et al. · arXiv:2304.06767 - [Ragas: Automated Evaluation of Retrieval Augmented Generation](https://md.research.elamur.ai/free/en/papers/es-2023-ragas-automated-evaluation-retrieval-augmented/) — Shahul Es, Jithin James, Luis Espinosa-Anke, et al. · arXiv:2309.15217 - [RARR: Researching and Revising What Language Models Say, Using Language Models](https://md.research.elamur.ai/free/en/papers/gao-2023-rarr-researching-revising-what-language/) — Luyu Gao, Zhuyun Dai, Panupong Pasupat, et al. · Proceedings of the 61st Annual Meeting of the… - [RECOMP: Improving Retrieval-Augmented LMs with Compression and Selective Augmentation](https://md.research.elamur.ai/free/en/papers/xu-2023-recomp-improving-retrieval-augmented-lms/) — Fangyuan Xu, Weijia Shi, Eunsol Choi · arXiv:2310.04408 - [Red teaming ChatGPT via Jailbreaking: Bias, Robustness, Reliability and Toxicity](https://md.research.elamur.ai/free/en/papers/zhuo-2023-red-teaming-chatgpt-jailbreaking-bias/) — Terry Yue Zhuo, Yujin Huang, Chunyang Chen, et al. · arXiv:2301.12867 - [Rediscovered Fragments Shed New Light on a Proto-Masoretic Torah Scroll](https://md.research.elamur.ai/free/en/papers/hbo-2023-sanders-rediscovered-fragments-shed-new-light/) — Paul Sanders · Ancient Hebrew - [REFINER: Reasoning Feedback on Intermediate Representations](https://md.research.elamur.ai/free/en/papers/paul-2023-refiner-reasoning-feedback-intermediate-representations/) — Debjit Paul, Mete Ismayilzada, Maxime Peyrard, et al. · arXiv:2304.01904 - [Reflexion: Language Agents with Verbal Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/shinn-2023-reflexion-language-agents-verbal-reinforcement/) — Noah Shinn, Federico Cassano, Edward Berman, et al. · arXiv:2303.11366 - [Reinforced Self-Training (ReST) for Language Modeling](https://md.research.elamur.ai/free/en/papers/gulcehre-2023-reinforced-self-training-rest-language/) — Caglar Gulcehre, Tom Le Paine, Srivatsan Srinivasan, et al. · arXiv:2308.08998 - [REPLUG: Retrieval-Augmented Black-Box Language Models](https://md.research.elamur.ai/free/en/papers/shi-2023-replug-retrieval-augmented-black-box/) — Weijia Shi, Sewon Min, Michihiro Yasunaga, et al. · arXiv:2301.12652 - [Representation Engineering: A Top-Down Approach to AI Transparency](https://md.research.elamur.ai/free/en/papers/zou-2023-representation-engineering-top-down-approach/) — Andy Zou, Long Phan, Sarah Chen, et al. · arXiv:2310.01405 - [RestGPT: Connecting Large Language Models with Real-World RESTful APIs](https://md.research.elamur.ai/free/en/papers/song-2023-restgpt-connecting-large-language-models/) — Yifan Song, Weimin Xiong, Dawei Zhu, et al. · arXiv:2306.06624 - [Results of WMT23 Metrics Shared Task: Metrics Might Be Guilty but References Are Not Innocent](https://md.research.elamur.ai/free/en/papers/freitag-2023-results-wmt23-metrics-shared-task/) — Markus Freitag, Nitika Mathur, Chi-kiu Lo, et al. · Proceedings of the Eighth Conference on Machine… - [Rethinking Benchmark and Contamination for Language Models with Rephrased Samples](https://md.research.elamur.ai/free/en/papers/yang-2023-rethinking-benchmark-contamination-language-models/) — Shuo Yang, Wei-Lin Chiang, Lianmin Zheng, et al. · arXiv:2311.04850 - [Retrieval meets Long Context Large Language Models](https://md.research.elamur.ai/free/en/papers/xu-2023-retrieval-meets-long-context-large/) — Peng Xu, Wei Ping, Xianchao Wu, et al. · arXiv:2310.03025 - [Retrieval-Augmented Generation for Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/gao-2023-retrieval-augmented-generation-large-language/) — Yunfan Gao, Yun Xiong, Xinyu Gao, et al. · arXiv:2312.10997 - [Ring Attention with Blockwise Transformers for Near-Infinite Context](https://md.research.elamur.ai/free/en/papers/liu-2023-ring-attention-blockwise-transformers-near/) — Hao Liu, Matei Zaharia, Pieter Abbeel · arXiv:2310.01889 - [Role-Play with Large Language Models](https://md.research.elamur.ai/free/en/papers/shanahan-2023-role-play-large-language-models/) — Murray Shanahan, Kyle McDonell, Laria Reynolds · arXiv:2305.16367 - [RoleLLM: Benchmarking, Eliciting, and Enhancing Role-Playing Abilities of Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2023-rolellm-benchmarking-eliciting-enhancing-role/) — Zekun Moore Wang, Zhongyuan Peng, Haoran Que, et al. · arXiv:2310.00746 - [RRHF: Rank Responses to Align Language Models with Human Feedback without tears](https://md.research.elamur.ai/free/en/papers/yuan-2023-rrhf-rank-responses-align-language/) — Zheng Yuan, Hongyi Yuan, Chuanqi Tan, et al. · arXiv:2304.05302 - [Safe RLHF: Safe Reinforcement Learning from Human Feedback](https://md.research.elamur.ai/free/en/papers/dai-2023-safe-rlhf-safe-reinforcement-learning/) — Josef Dai, Xuehai Pan, Ruiyang Sun, et al. · arXiv:2310.12773 - [Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow Instructions](https://md.research.elamur.ai/free/en/papers/bianchi-2023-safety-tuned-llamas-lessons-improving/) — Federico Bianchi, Mirac Suzgun, Giuseppe Attanasio, et al. · arXiv:2309.07875 - [SafetyBench: Evaluating the Safety of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2023-safetybench-evaluating-safety-large/) — Zhexin Zhang, Leqi Lei, Lindong Wu, et al. · arXiv:2309.07045 - [SALMONN: Towards Generic Hearing Abilities for Large Language Models](https://md.research.elamur.ai/free/en/papers/tang-2023-salmonn-towards-generic-hearing-abilities/) — Changli Tang, Wenyi Yu, Guangzhi Sun, et al. · arXiv:2310.13289 - [SantaCoder: don't reach for the stars!](https://md.research.elamur.ai/free/en/papers/allal-2023-santacoder-don-t-reach-stars/) — Loubna Ben Allal, Raymond Li, Denis Kocetkov, et al. · arXiv:2301.03988 - [Scalable Extraction of Training Data from (Production) Language Models](https://md.research.elamur.ai/free/en/papers/nasr-2023-scalable-extraction-training-data-production/) — Milad Nasr, Nicholas Carlini, Jonathan Hayase, et al. · arXiv:2311.17035 - [Scaling Relationship on Learning Mathematical Reasoning with Large Language Models](https://md.research.elamur.ai/free/en/papers/yuan-2023-scaling-relationship-learning-mathematical-reasoning/) — Zheng Yuan, Hongyi Yuan, Chengpeng Li, et al. · arXiv:2308.01825 - [Scaling Speech Technology to 1,000+ Languages](https://md.research.elamur.ai/free/en/papers/pratap-2023-scaling-speech-technology-1-000/) — Vineel Pratap, Andros Tjandra, Bowen Shi, et al. · arXiv:2305.13516 - [Scaling up CometKiwi: Unbabel-IST 2023 Submission for the Quality Estimation Shared Task](https://md.research.elamur.ai/free/en/papers/rei-2023-scaling-up-cometkiwi-unbabel-ist/) — Ricardo Rei, Nuno M. Guerreiro, José Pombal, et al. · Proceedings of the Eighth Conference on Machine… - [SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2023-scibench-evaluating-college-level-scientific/) — Xiaoxuan Wang, Ziniu Hu, Pan Lu, et al. · arXiv:2307.10635 - [Scoring Coreference Chains with Split-Antecedent Anaphors](https://md.research.elamur.ai/free/en/papers/paun-2023-scoring-coreference-chains-split-antecedent/) — Silviu Paun, Juntao Yu, Nafise Sadat Moosavi, et al. · English - [SCOTT: Self-Consistent Chain-of-Thought Distillation](https://md.research.elamur.ai/free/en/papers/wang-2023-scott-self-consistent-chain-thought/) — Peifeng Wang, Zhengyang Wang, Zheng Li, et al. · Proceedings of the 61st Annual Meeting of the… - [SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis](https://md.research.elamur.ai/free/en/papers/podell-2023-sdxl-improving-latent-diffusion-models/) — Dustin Podell, Zion English, Kyle Lacey, et al. · arXiv:2307.01952 - [Seamless: Multilingual Expressive and Streaming Speech Translation](https://md.research.elamur.ai/free/en/papers/communication-2023-seamless-multilingual-expressive-streaming-speech/) — Seamless Communication, Loic Barrault, Yu-An Chung, et al. · arXiv:2312.05187 - [SeamlessM4T: Massively Multilingual & Multimodal Machine Translation](https://md.research.elamur.ai/free/en/papers/communication-2023-seamlessm4t-massively-multilingual-multimodal-machine/) — Seamless Communication, Loic Barrault, Yu-An Chung, et al. · arXiv:2308.11596 - [Secrets of RLHF in Large Language Models Part I: PPO](https://md.research.elamur.ai/free/en/papers/zheng-2023-secrets-rlhf-large-language-models/) — Rui Zheng, Shihan Dou, Songyang Gao, et al. · arXiv:2307.04964 - [SEED-Bench: Benchmarking Multimodal LLMs with Generative Comprehension](https://md.research.elamur.ai/free/en/papers/li-2023-seed-bench-benchmarking-multimodal-llms/) — Bohao Li, Rui Wang, Guangzhi Wang, et al. · arXiv:2307.16125 - [Segment Anything](https://md.research.elamur.ai/free/en/papers/kirillov-2023-segment-anything/) — Alexander Kirillov, Eric Mintun, Nikhila Ravi, et al. · arXiv:2304.02643 - [Self-Alignment with Instruction Backtranslation](https://md.research.elamur.ai/free/en/papers/li-2023-self-alignment-instruction-backtranslation/) — Xian Li, Ping Yu, Chunting Zhou, et al. · arXiv:2308.06259 - [Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigation](https://md.research.elamur.ai/free/en/papers/mundler-2023-self-contradictory-hallucinations-large-language/) — Niels Mundler, Jingxuan He, Slobodan Jenko, et al. · arXiv:2305.15852 - [Self-Evaluation Guided Beam Search for Reasoning](https://md.research.elamur.ai/free/en/papers/xie-2023-self-evaluation-guided-beam-search/) — Yuxi Xie, Kenji Kawaguchi, Yiran Zhao, et al. · arXiv:2305.00633 - [Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection](https://md.research.elamur.ai/free/en/papers/asai-2023-self-rag-learning-retrieve-generate/) — Akari Asai, Zeqiu Wu, Yizhong Wang, et al. · arXiv:2310.11511 - [SemDeDup: Data-efficient learning at web-scale through semantic deduplication](https://md.research.elamur.ai/free/en/papers/abbas-2023-semdedup-data-efficient-learning-web/) — Amro Abbas, Kushal Tirumala, Dániel Simig, et al. · arXiv:2303.09540 - [SemEval-2023 Task 10: Explainable Detection of Online Sexism](https://md.research.elamur.ai/free/en/papers/kirk-2023-semeval-2023-task-10-explainable/) — Hannah Kirk, Wenjie Yin, Bertie Vidgen, et al. · Proceedings of the 17th International Workshop… - [Sentiment Analysis Dataset in Moroccan Dialect: Bridging the Gap Between Arabic and Latin Scripted dialect](https://md.research.elamur.ai/free/en/papers/jbel-2023-sentiment-analysis-dataset-moroccan-dialect/) — Mouad Jbel, Mourad Jabrane, Imad Hafidi, et al. · arXiv:2303.15987 - [Sentiment Analysis in the Era of Large Language Models: A Reality Check](https://md.research.elamur.ai/free/en/papers/zhang-2023-sentiment-analysis-era-large-language/) — Wenxuan Zhang, Yue Deng, Bing Liu, et al. · arXiv:2305.15005 - [Seq2seq is All You Need for Coreference Resolution](https://md.research.elamur.ai/free/en/papers/zhang-2023-seq2seq-is-all-you-need/) — Wenzheng Zhang, Sam Wiseman, Karl Stratos · Proceedings of the 2023 Conference on Empirical… - 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