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Found 9 papers, 8 papers with code
Hierarchical Indexing for Retrieval-Augmented Opinion Summarization
We show that HIRO learns an encoding space that is more semantically structured than prior work, and generates summaries that are more representative of the opinions in the input reviews.
Human Feedback is not Gold Standard
We critically analyse the use of human feedback for both training and evaluation, to verify whether it fully captures a range of crucial error criteria.
Optimal Transport Posterior Alignment for Cross-lingual Semantic Parsing
Cross-lingual semantic parsing transfers parsing capability from a high-resource language (e. g., English) to low-resource languages with scarce training data.
Attributable and Scalable Opinion Summarization
We propose a method for unsupervised opinion summarization that encodes sentences from customer reviews into a hierarchical discrete latent space, then identifies common opinions based on the frequency of their encodings.
Hierarchical Sketch Induction for Paraphrase Generation
We propose a generative model of paraphrase generation, that encourages syntactic diversity by conditioning on an explicit syntactic sketch.
Ranked #1 on
Paraphrase Generation
on Paralex
Factorising Meaning and Form for Intent-Preserving Paraphrasing
We propose a method for generating paraphrases of English questions that retain the original intent but use a different surface form.
Ranked #2 on
Paraphrase Generation
on Paralex
Querent Intent in Multi-Sentence Questions
Multi-sentence questions (MSQs) are sequences of questions connected by relations which, unlike sequences of standalone questions, need to be answered as a unit.
Evaluating Rewards for Question Generation Models
Recent approaches to question generation have used modifications to a Seq2Seq architecture inspired by advances in machine translation.
Ranked #12 on
Question Generation
on SQuAD1.1
Assumption Questioning: Latent Copying and Reward Exploitation in Question Generation
Question generation is an important task for improving our ability to process natural language data, with additional challenges over other sequence transformation tasks.
