Search Results - "Mao, Yuning"

Extremely facile preparation of high-performance Fe2O3 anode for lithium-ion batteries by Li, Zhiyang, Mao, Yuning, Tian, Qinghua, Zhang, Wei, Yang, Li

“…As the concept of promoting environmental protection and energy conservation becomes more and more popular, reasonably green approaches for preparing…”
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Improving the lithium storage performance of SnO2 nanoparticles by in-situ embedding into a porous carbon framework by Mao, Yuning, Tian, Qinghua, Chen, Fengtao, Chen, Jizhang, Yang, Li

“…Wide attention has been recently paid to the potential application of nanosized SnO2 material in lithium-ion batteries as a new high performance anode owe to…”
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Heterogeneous nanocrystals assembled TiO2/SnO2/C composite for improved lithium storage by Tian, Qinghua, Mao, Yuning, Zhang, Xuzhen, Yang, Li

“…•Heterogeneous nanocrystals assembled TiO2/SnO2/C composite was prepared.•It was endowed with outstanding advantages in lithium storage by the unique…”
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Guided Text Summarization With Limited Supervision by Mao, Yuning

“…In the information age, people are surrounded by a massive amount of texts in daily life. It has become increasingly difficult to acquire desirable, salient,…”
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Simulating Online Social Response: A Stimulus/Response Perspective by Shao, Huajie, Abdelzaher, Tarek, Han, Jiawei, Jiang, Minhao, Mao, Yuning, Meng, Yu, Qiu, Wenda, Sun, Dachun, Wang, Ruijie, Yang, Chaoqi, Yang, Zhenzhou, Zhang, Xinyang, Zhang, Yu, Cohen, Sam, Flamino, James, Korniss, Gyorgy, Malik, Omar, Mandviwalla, Aamir, Szymanski, Boleslaw, Yin, Lake

“…The paper describes a methodology for simulating online social media activities that occur in response to external events. A large number of social media…”
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CiteSum: Citation Text-guided Scientific Extreme Summarization and Domain Adaptation with Limited Supervision by Mao, Yuning, Zhong, Ming, Han, Jiawei

“…Scientific extreme summarization (TLDR) aims to form ultra-short summaries of scientific papers. Previous efforts on curating scientific TLDR datasets failed…”
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SAIS: Supervising and Augmenting Intermediate Steps for Document-Level Relation Extraction by Xiao, Yuxin, Zhang, Zecheng, Mao, Yuning, Yang, Carl, Han, Jiawei

“…Stepping from sentence-level to document-level, the research on relation extraction (RE) confronts increasing text length and more complicated entity…”
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Residual Prompt Tuning: Improving Prompt Tuning with Residual Reparameterization by Razdaibiedina, Anastasia, Mao, Yuning, Hou, Rui, Khabsa, Madian, Lewis, Mike, Ba, Jimmy, Almahairi, Amjad

“…Prompt tuning is one of the successful approaches for parameter-efficient tuning of pre-trained language models. Despite being arguably the most…”
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Eider: Empowering Document-level Relation Extraction with Efficient Evidence Extraction and Inference-stage Fusion by Xie, Yiqing, Shen, Jiaming, Li, Sha, Mao, Yuning, Han, Jiawei

“…Document-level relation extraction (DocRE) aims to extract semantic relations among entity pairs in a document. Typical DocRE methods blindly take the full…”
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Progressive Prompts: Continual Learning for Language Models by Razdaibiedina, Anastasia, Mao, Yuning, Hou, Rui, Khabsa, Madian, Lewis, Mike, Almahairi, Amjad

“…We introduce Progressive Prompts - a simple and efficient approach for continual learning in language models. Our method allows forward transfer and resists…”
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XLM-V: Overcoming the Vocabulary Bottleneck in Multilingual Masked Language Models by Liang, Davis, Gonen, Hila, Mao, Yuning, Hou, Rui, Goyal, Naman, Ghazvininejad, Marjan, Zettlemoyer, Luke, Khabsa, Madian

“…Large multilingual language models typically rely on a single vocabulary shared across 100+ languages. As these models have increased in parameter count and…”
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RoAST: Robustifying Language Models via Adversarial Perturbation with Selective Training by Kim, Jaehyung, Mao, Yuning, Hou, Rui, Yu, Hanchao, Liang, Davis, Fung, Pascale, Wang, Qifan, Feng, Fuli, Huang, Lifu, Khabsa, Madian

“…Fine-tuning pre-trained language models (LMs) has become the de facto standard in many NLP tasks. Nevertheless, fine-tuned LMs are still prone to robustness…”
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Improving Model Factuality with Fine-grained Critique-based Evaluator by Xie, Yiqing, Zhou, Wenxuan, Prakash, Pradyot, Jin, Di, Mao, Yuning, Fettes, Quintin, Talebzadeh, Arya, Wang, Sinong, Fang, Han, Rose, Carolyn, Fried, Daniel, Zhang, Hejia

“…Factuality evaluation aims to detect factual errors produced by language models (LMs) and hence guide the development of more factual models. Towards this…”
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Extract, Denoise and Enforce: Evaluating and Improving Concept Preservation for Text-to-Text Generation by Mao, Yuning, Ma, Wenchang, Lei, Deren, Han, Jiawei, Ren, Xiang

“…Prior studies on text-to-text generation typically assume that the model could figure out what to attend to in the input and what to include in the output via…”
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MART: Improving LLM Safety with Multi-round Automatic Red-Teaming by Ge, Suyu, Zhou, Chunting, Hou, Rui, Khabsa, Madian, Wang, Yi-Chia, Wang, Qifan, Han, Jiawei, Mao, Yuning

“…Red-teaming is a common practice for mitigating unsafe behaviors in Large Language Models (LLMs), which involves thoroughly assessing LLMs to identify…”
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Constrained Abstractive Summarization: Preserving Factual Consistency with Constrained Generation by Mao, Yuning, Ren, Xiang, Ji, Heng, Han, Jiawei

“…Despite significant progress, state-of-the-art abstractive summarization methods are still prone to hallucinate content inconsistent with the source document…”
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Multi-document Summarization with Maximal Marginal Relevance-guided Reinforcement Learning by Mao, Yuning, Qu, Yanru, Xie, Yiqing, Ren, Xiang, Han, Jiawei

“…While neural sequence learning methods have made significant progress in single-document summarization (SDS), they produce unsatisfactory results on…”
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Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts by Samvelyan, Mikayel, Raparthy, Sharath Chandra, Lupu, Andrei, Hambro, Eric, Markosyan, Aram H, Bhatt, Manish, Mao, Yuning, Jiang, Minqi, Parker-Holder, Jack, Foerster, Jakob, Rocktäschel, Tim, Raileanu, Roberta

“…As large language models (LLMs) become increasingly prevalent across many real-world applications, understanding and enhancing their robustness to adversarial…”
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Representation Deficiency in Masked Language Modeling by Meng, Yu, Krishnan, Jitin, Wang, Sinong, Wang, Qifan, Mao, Yuning, Fang, Han, Ghazvininejad, Marjan, Han, Jiawei, Zettlemoyer, Luke

“…Masked Language Modeling (MLM) has been one of the most prominent approaches for pretraining bidirectional text encoders due to its simplicity and…”
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Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations by Inan, Hakan, Upasani, Kartikeya, Chi, Jianfeng, Rungta, Rashi, Iyer, Krithika, Mao, Yuning, Tontchev, Michael, Hu, Qing, Fuller, Brian, Testuggine, Davide, Khabsa, Madian

“…We introduce Llama Guard, an LLM-based input-output safeguard model geared towards Human-AI conversation use cases. Our model incorporates a safety risk…”
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