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Found 3 papers, 2 papers with code
EROS: Entity-Driven Controlled Policy Document Summarization
In this paper, we propose to enhance the interpretability and readability of policy documents by using controlled abstractive summarization -- we enforce the generated summaries to include critical privacy-related entities (e. g., data and medium) and organization's rationale (e. g., target and reason) in collecting those entities.
How to think step-by-step: A mechanistic understanding of chain-of-thought reasoning
Despite superior reasoning prowess demonstrated by Large Language Models (LLMs) with Chain-of-Thought (CoT) prompting, a lack of understanding prevails around the internal mechanisms of the models that facilitate CoT generation.
Frugal LMs Trained to Invoke Symbolic Solvers Achieve Parameter-Efficient Arithmetic Reasoning
In this paper, we start with the hypothesis that much smaller LMs, which are weak at multi-step reasoning, can achieve reasonable arithmetic reasoning if arithmetic word problems are posed as a formalize-then-solve task.
Ranked #11 on
Math Word Problem Solving
on SVAMP
(using extra training data)
