Iterated decomposition: Improving science q&a by supervising reasoning processes
J Reppert, B Rachbach, C George, L Stebbing… - arXiv preprint arXiv …, 2023 - arxiv.org
Language models (LMs) can perform complex reasoning either end-to-end, with hidden
latent state, or compositionally, with transparent intermediate state. Composition offers …
latent state, or compositionally, with transparent intermediate state. Composition offers …
ChartThinker: A Contextual Chain-of-Thought Approach to Optimized Chart Summarization
Data visualization serves as a critical means for presenting data and mining its valuable
insights. The task of chart summarization, through natural language processing techniques …
insights. The task of chart summarization, through natural language processing techniques …
GenDec: A robust generative Question-decomposition method for Multi-hop reasoning
Multi-hop QA (MHQA) involves step-by-step reasoning to answer complex questions and
find multiple relevant supporting facts. However, Existing large language models'(LLMs) …
find multiple relevant supporting facts. However, Existing large language models'(LLMs) …
Exploratory inference chain: Exploratorily chaining multi-hop inferences with large language models for question-answering
S Haji, K Suekane, H Sano… - 2023 IEEE 17th …, 2023 - ieeexplore.ieee.org
Successful few-shot question-answering with large language models (LLMs) has been
reported for a variety of tasks. In the usual approach, an answer is generated by a single call …
reported for a variety of tasks. In the usual approach, an answer is generated by a single call …
Uncertainty Guided Global Memory Improves Multi-Hop Question Answering
A Sagirova, M Burtsev - Proceedings of the 2023 Conference on …, 2023 - aclanthology.org
Transformers have become the gold standard for many natural language processing tasks
and, in particular, for multi-hop question answering (MHQA). This task includes processing a …
and, in particular, for multi-hop question answering (MHQA). This task includes processing a …
Long-form Question Answering: An Iterative Planning-Retrieval-Generation Approach
Long-form question answering (LFQA) poses a challenge as it involves generating detailed
answers in the form of paragraphs, which go beyond simple yes/no responses or short …
answers in the form of paragraphs, which go beyond simple yes/no responses or short …
Multi-hop Attention GNN with Answer-Evidence Contrastive Loss for Multi-hop QA
N Yang, M Yang - 2023 International Joint Conference on …, 2023 - ieeexplore.ieee.org
Multi-hop question answering (QA) is a challenging task in natural language processing
(NLP), which requires multi-step reasoning over the sentences from several passages and …
(NLP), which requires multi-step reasoning over the sentences from several passages and …