Jointly training multi-hop question generation with question answering through alignment and contrastive losses improves generated question quality on HotpotQA and MuSiQue over vanilla backbones.
Semantic Graphs for Generating Deep Questions
5 Pith papers cite this work, alongside 79 external citations. Polarity classification is still indexing.
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AI claim verification models rely on salient-constraint shortcuts instead of full compositional reasoning under the closed-world assumption, as revealed by their over-acceptance of claims with supported salient constraints but contradicted non-salient ones.
A dual-perspective keyword guidance framework with two decoders improves multi-hop question generation over prior keyword-based methods.
In a proprietary rule-based NLG system, NMT-assisted grammar transfer required post-editing of roughly 19% of grammar units across seven target languages in a small human evaluation.
A tree-of-thoughts inspired hybrid extractive-abstractive LLM prompt yields better legal case judgment summaries than standard extractive or abstractive prompts.
citing papers explorer
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When Verification Fails: How Compositionally Infeasible Claims Escape Rejection
AI claim verification models rely on salient-constraint shortcuts instead of full compositional reasoning under the closed-world assumption, as revealed by their over-acceptance of claims with supported salient constraints but contradicted non-salient ones.
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A Tree-of-Thoughts Inspired Hybrid Approach for Legal Case Judgement Summarization using LLMs
A tree-of-thoughts inspired hybrid extractive-abstractive LLM prompt yields better legal case judgment summaries than standard extractive or abstractive prompts.