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Large Language Models as Zero-shot Dialogue State Tracker through Function Calling
Annual Meeting of the Association for Computational LinguisticsLarge language models (LLMs) are increasingly prevalent in conversational systems due to their advanced understanding and generative capabilities in general contexts.
Zekun Li +9 more
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Rethinking Task-Oriented Dialogue Systems: From Complex Modularity to Zero-Shot Autonomous Agent
Annual Meeting of the Association for Computational LinguisticsTask-oriented dialogue (TOD) systems are pre-001 dominantly designed to be composed of several 002 functional modules (e.g. dialogue state tracker, 003 dialogue policy, natural language generation) 004 whether they are pipeline or end-to-end archi-005 ...
Heng-Da Xu +4 more
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ListT5: Listwise Reranking with Fusion-in-Decoder Improves Zero-shot Retrieval
Annual Meeting of the Association for Computational LinguisticsWe propose ListT5, a novel reranking approach based on Fusion-in-Decoder (FiD) that handles multiple candidate passages at both train and inference time.
Soyoung Yoon +5 more
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Self-Improving for Zero-Shot Named Entity Recognition with Large Language Models
North American Chapter of the Association for Computational Linguistics, 2023Exploring the application of powerful large language models (LLMs) on the named entity recognition (NER) task has drawn much attention recently. This work pushes the performance boundary of zero-shot NER with LLMs by proposing a training-free self ...
Tingyu Xie +4 more
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Zero-Revelation RegTech: Detecting Risk through Linguistic Analysis of Corporate Emails and News
The Journal of Financial Data Science, 2017Natural language processing is a fast-growing area of data science for the finance industry. The authors demonstrate how an applied linguistics expert system may be used to parse corporate email content and news to assess factors that predict escalating risk or the gradual shifting of other critical characteristics within the firm before they manifest ...
Sanjiv Ranjan Das +2 more
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TCSinger 2: Customizable Multilingual Zero-shot Singing Voice Synthesis
Annual Meeting of the Association for Computational LinguisticsCustomizable multilingual zero-shot singing voice synthesis (SVS) has various potential applications in music composition and short video dubbing.
Yu Zhang +8 more
semanticscholar +1 more source
Journal of Applied Statistics, 2019
Corpus linguistics is the study of language as expressed in a body of texts or documents. The relative frequency of a word within a text and the dispersion of the word across the collection of texts provide information about the word's prominence and diffusion, respectively.
Brent, Burch, Jesse, Egbert
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Corpus linguistics is the study of language as expressed in a body of texts or documents. The relative frequency of a word within a text and the dispersion of the word across the collection of texts provide information about the word's prominence and diffusion, respectively.
Brent, Burch, Jesse, Egbert
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Learning to Generate Instruction Tuning Datasets for Zero-Shot Task Adaptation
Annual Meeting of the Association for Computational LinguisticsWe introduce Bonito, an open-source model for conditional task generation that converts unannotated text into task-specific training datasets for instruction tuning.
Nihal V. Nayak +3 more
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Who Wrote This? The Key to Zero-Shot LLM-Generated Text Detection Is GECScore
International Conference on Computational LinguisticsThe efficacy of detectors for texts generated by large language models (LLMs) substantially depends on the availability of large-scale training data. However, white-box zero-shot detectors, which require no such data, are limited by the accessibility of ...
Junchao Wu +6 more
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The linguistics of zero: A cognitive reference point or a phantom?
Folia Linguistica, 2009Insights from cognitive psychology indicate that the zero value on a scale is an important reference-point phenomenon in the processing of relative adjectives. However, linguistic evidence for the reference-point status of the zero value has not been provided hitherto.
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