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Found 7 papers, 4 papers with code
Synthetic Prompting: Generating Chain-of-Thought Demonstrations for Large Language Models
However, the quality of the prompts depends on the demonstrations given to the models, and creating many of them by hand is costly.
Chaining Simultaneous Thoughts for Numerical Reasoning
Given that rich information is hidden behind ubiquitous numbers in text, numerical reasoning over text should be an essential skill of AI systems.
Answering Open-Domain Multi-Answer Questions via a Recall-then-Verify Framework
Open-domain questions are likely to be open-ended and ambiguous, leading to multiple valid answers.
A Mutual Information Maximization Approach for the Spurious Solution Problem in Weakly Supervised Question Answering
This setting gives rise to the spurious solution problem: there may exist many spurious solutions that coincidentally derive the correct answer, but training on such solutions can hurt model performance (e. g., producing wrong solutions or answers).
AdvExpander: Generating Natural Language Adversarial Examples by Expanding Text
In this paper, we present AdvExpander, a method that crafts new adversarial examples by expanding text, which is complementary to previous substitution-based methods.
CoTK: An Open-Source Toolkit for Fast Development and Fair Evaluation of Text Generation
In text generation evaluation, many practical issues, such as inconsistent experimental settings and metric implementations, are often ignored but lead to unfair evaluation and untenable conclusions.
Long and Diverse Text Generation with Planning-based Hierarchical Variational Model
Existing neural methods for data-to-text generation are still struggling to produce long and diverse texts: they are insufficient to model input data dynamically during generation, to capture inter-sentence coherence, or to generate diversified expressions.
