215 citations · 330 across the 35 of their papers we have counts for
5 papers · 1 filter
ProofWriter: Generating Implications, Proofs, and Abductive Statements over Natural Language
Oyvind Tafjord, Bhavana Dalvi Mishra, Peter Clark
Transformers have been shown to emulate logical deduction over natural language theories (logical rules expressed in natural language), reliably assigning true/false labels to cand…
Leap-Of-Thought: Teaching Pre-Trained Models to Systematically Reason Over Implicit Knowledge
Alon Talmor, Oyvind Tafjord, Peter Clark +2
To what extent can a neural network systematically reason over symbolic facts? Evidence suggests that large pre-trained language models (LMs) acquire some reasoning capacity, but t…
UnifiedQA: Crossing Format Boundaries With a Single QA System
Daniel Khashabi, Sewon Min, Tushar Khot +4
Question answering (QA) tasks have been posed using a variety of formats, such as extractive span selection, multiple choice, etc. This has led to format-specialized models, and ev…
"You are grounded!": Latent Name Artifacts in Pre-trained Language Models
Vered Shwartz, Rachel Rudinger, Oyvind Tafjord
Pre-trained language models (LMs) may perpetuate biases originating in their training corpus to downstream models. We focus on artifacts associated with the representation of given…
Transformers as Soft Reasoners over Language
Peter Clark, Oyvind Tafjord, Kyle Richardson
Beginning with McCarthy's Advice Taker (1959), AI has pursued the goal of providing a system with explicit, general knowledge and having the system reason over that knowledge. Howe…