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Found 8 papers, 1 papers with code
Conversational Search with Mixed-Initiative - Asking Good Clarification Questions backed-up by Passage Retrieval
We deal with the scenario of conversational search, where user queries are under-specified or ambiguous.
When LLMs are Unfit Use FastFit: Fast and Effective Text Classification with Many Classes
We present FastFit, a method, and a Python package design to provide fast and accurate few-shot classification, especially for scenarios with many semantically similar classes.
Genie: Achieving Human Parity in Content-Grounded Datasets Generation
Furthermore, we compare models trained on our data with models trained on human-written data -- ELI5 and ASQA for LFQA and CNN-DailyMail for Summarization.
QAID: Question Answering Inspired Few-shot Intent Detection
Intent detection with semantically similar fine-grained intents is a challenging task.
Evaluating and Improving the Coreference Capabilities of Machine Translation Models
Machine translation (MT) requires a wide range of linguistic capabilities, which current end-to-end models are expected to learn implicitly by observing aligned sentences in bilingual corpora.
Reinforcement Learning with Large Action Spaces for Neural Machine Translation
Applying Reinforcement learning (RL) following maximum likelihood estimation (MLE) pre-training is a versatile method for enhancing neural machine translation (NMT) performance.
Conversational Search with Mixed-Initiative -- Asking Good Clarification Questions backed-up by Passage Retrieval
We deal with the scenario of conversational search, where user queries are under-specified or ambiguous.
Filling the Gaps in Ancient Akkadian Texts: A Masked Language Modelling Approach
We present models which complete missing text given transliterations of ancient Mesopotamian documents, originally written on cuneiform clay tablets (2500 BCE - 100 CE).
