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检索条件"任意字段=Conference on empirical methods in natural language processing"
15135 条 记 录,以下是251-260 订阅
排序:
Can Large language Models Faithfully Express Their Intrinsic Uncertainty in Words?
Can Large Language Models Faithfully Express Their Intrinsic...
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2024 conference on empirical methods in natural language processing, EMNLP 2024
作者: Yona, Gal Aharoni, Roee Geva, Mor Google Research United States Tel Aviv University Israel
We posit that large language models (LLMs) should be capable of expressing their intrinsic uncertainty in natural language. For example, if the LLM is equally likely to output two contradicting answers to the same que... 详细信息
来源: 评论
LIONs: An empirically Optimized Approach to Align language Models
LIONs: An Empirically Optimized Approach to Align Language M...
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2024 conference on empirical methods in natural language processing, EMNLP 2024
作者: Yu, Xiao Wu, Qingyang Li, Yu Yu, Zhou Columbia University United States
Alignment is a crucial step to enhance the instruction-following and conversational abilities of language models. Despite many recent work proposing new algorithms, datasets, and training pipelines, there is a lack of... 详细信息
来源: 评论
Generating Demonstrations for In-Context Compositional Generalization in Grounded language Learning
Generating Demonstrations for In-Context Compositional Gener...
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2024 conference on empirical methods in natural language processing, EMNLP 2024
作者: Spilsbury, Sam Marttinen, Pekka Ilin, Alexander Dept. of Computer Science Aalto University Espoo Finland
In-Context-learning and few-shot prompting are viable methods compositional output generation. However, these methods can be very sensitive to the choice of support examples used. Retrieving good supports from the tra... 详细信息
来源: 评论
Mirages. On Anthropomorphism in Dialogue Systems
Mirages. On Anthropomorphism in Dialogue Systems
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conference on empirical methods in natural language processing (EMNLP)
作者: Abercrombie, Gavin Curry, Amanda Cercas Dinkar, Tanvi Rieser, Verena Talat, Zeerak Heriot Watt Univ Edinburgh Midlothian Scotland Bocconi Univ Milan Italy Mohamed Bin Zayed Univ Artificial Intelligence Abu Dhabi U Arab Emirates Google DeepMind London England
Automated dialogue or conversational systems are anthropomorphised by developers and personified by users. While a degree of anthropomorphism may be inevitable due to the choice of medium, conscious and unconscious de... 详细信息
来源: 评论
CONVERSATION CHRONICLES: Towards Diverse Temporal and Relational Dynamics in Multi-Session Conversations
CONVERSATION CHRONICLES: Towards Diverse Temporal and Relati...
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conference on empirical methods in natural language processing (EMNLP)
作者: Jang, Jihyoung Boo, Minseong Kim, Hyounghun UNIST Artificial Intelligence Grad Sch Ulsan South Korea
In the field of natural language processing, open-domain chatbots have emerged as an important research topic. However, a major limitation of existing open-domain chatbot research is its singular focus on short single... 详细信息
来源: 评论
Calibrating language Models with Adaptive Temperature Scaling
Calibrating Language Models with Adaptive Temperature Scalin...
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2024 conference on empirical methods in natural language processing, EMNLP 2024
作者: Xie, Johnathan Chen, Annie S. Lee, Yoonho Mitchell, Eric Finn, Chelsea Stanford University United States
The effectiveness of large language models (LLMs) is not only measured by their ability to generate accurate outputs but also by their calibration-how well their confidence scores reflect the probability of their outp... 详细信息
来源: 评论
Predicting generalization performance with correctness discriminators
Predicting generalization performance with correctness discr...
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2024 conference on empirical methods in natural language processing, EMNLP 2024
作者: Yao, Yuekun Koller, Alexander Department of Language Science and Technology Saarland University Saarland Informatics Campus Saarbrücken Germany
The ability to predict an NLP model's accuracy on unseen, potentially out-of-distribution data is a prerequisite for trustworthiness. We present a novel model that establishes upper and lower bounds on the accurac... 详细信息
来源: 评论
APoLLo : Unified Adapter and Prompt Learning for Vision language Models
APoLLo : Unified Adapter and Prompt Learning for Vision Lang...
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conference on empirical methods in natural language processing (EMNLP)
作者: Chowdhury, Sanjoy Nag, Sayan Manocha, Dinesh Univ Maryland College Pk MD 20742 USA Univ Toronto Toronto ON Canada
The choice of input text prompt plays a critical role in the performance of Vision-language Pretrained (VLP) models such as CLIP. We present APoLLo, a unified multi-modal approach that combines Adapter and Prompt lear... 详细信息
来源: 评论
Direct Multi-Turn Preference Optimization for language Agents
Direct Multi-Turn Preference Optimization for Language Agent...
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2024 conference on empirical methods in natural language processing, EMNLP 2024
作者: Shi, Wentao Yuan, Mengqi Wu, Junkang Wang, Qifan Feng, Fuli University of Science and Technology of China China Meta AI United States
Adapting Large language Models (LLMs) for agent tasks is critical in developing language agents. Direct Preference Optimization (DPO) is a promising technique for this adaptation with the alleviation of compounding er... 详细信息
来源: 评论
Interactive Text-to-SQL Generation via Editable Step-by-Step Explanations
Interactive Text-to-SQL Generation via Editable Step-by-Step...
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conference on empirical methods in natural language processing (EMNLP)
作者: Tian, Yuan Zhang, Zheng Ning, Zheng Li, Toby Jia-Jun Kummerfeld, Jonathan K. Zhang, Tianyi Purdue Univ W Lafayette IN 47907 USA Univ Notre Dame Notre Dame IN 46556 USA Univ Sydney Sydney NSW Australia
Relational databases play an important role in business, science, and more. However, many users cannot fully unleash the analytical power of relational databases, because they are not familiar with database languages ... 详细信息
来源: 评论