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Found 5 papers, 2 papers with code
STRUM-LLM: Attributed and Structured Contrastive Summarization
Users often struggle with decision-making between two options (A vs B), as it usually requires time-consuming research across multiple web pages.
ReST meets ReAct: Self-Improvement for Multi-Step Reasoning LLM Agent
Answering complex natural language questions often necessitates multi-step reasoning and integrating external information.
Ranked #1 on
Question Answering
on Bamboogle
LogicInference: A New Dataset for Teaching Logical Inference to seq2seq Models
Machine learning models such as Transformers or LSTMs struggle with tasks that are compositional in nature such as those involving reasoning/inference.
Making Transformers Solve Compositional Tasks
Several studies have reported the inability of Transformer models to generalize compositionally, a key type of generalization in many NLP tasks such as semantic parsing.
ETC: Encoding Long and Structured Inputs in Transformers
Transformer models have advanced the state of the art in many Natural Language Processing (NLP) tasks.
Ranked #3 on
Question Answering
on ConditionalQA
