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Found 11 papers, 4 papers with code
Crafting a Good Prompt or Providing Exemplary Dialogues? A Study of In-Context Learning for Persona-based Dialogue Generation
Previous in-context learning (ICL) research has focused on tasks such as classification, machine translation, text2table, etc., while studies on whether ICL can improve human-like dialogue generation are scarce.
Examining the Effect of Pre-training on Time Series Classification
(iv) Adding more pre-training data does not improve generalization, but it can strengthen the advantage of pre-training on the original data volume, such as faster convergence.
Sudowoodo: a Chinese Lyric Imitation System with Source Lyrics
In this paper, we introduce \textbf{\textit{Sudowoodo}}, a Chinese lyrics imitation system that can generate new lyrics based on the text of source lyrics.
I-WAS: a Data Augmentation Method with GPT-2 for Simile Detection
Simile detection is a valuable task for many natural language processing (NLP)-based applications, particularly in the field of literature.
Neighborhood-based Hard Negative Mining for Sequential Recommendation
Motivated by this observation, we propose a Graph-based Negative sampling approach based on Neighborhood Overlap (GNNO) to exploit structural information hidden in user behaviors for negative mining.
Unraveling the Mystery of Artifacts in Machine Generated Text
As neural Text Generation Models (TGM) have become more and more capable of generating text indistinguishable from human-written ones, the misuse of text generation technologies can have serious ramifications.
Probing Simile Knowledge from Pre-trained Language Models
In this paper, we probe simile knowledge from PLMs to solve the SI and SG tasks in the unified framework of simile triple completion for the first time.
Unsupervised Representation Learning of Player Behavioral Data with Confidence Guided Masking
Players of online games generate rich behavioral data during gaming.
Dialog Intent Induction via Density-based Deep Clustering Ensemble
Existing task-oriented chatbots heavily rely on spoken language understanding (SLU) systems to determine a user's utterance's intent and other key information for fulfilling specific tasks.
Taming Repetition in Dialogue Generation
The wave of pre-training language models has been continuously improving the quality of the machine-generated conversations, however, some of the generated responses still suffer from excessive repetition, sometimes repeating words from utterance, sometimes repeating words within self-generated responses, or both.
Fake news stance detection using stacked ensemble of classifiers
Fake news has become a hotly debated topic in journalism.
