Search Results for author:
Found 8 papers, 5 papers with code
NovaCOMET: Open Commonsense Foundation Models with Symbolic Knowledge Distillation
We present NovaCOMET, an open commonsense knowledge model, that combines the best aspects of knowledge and general task models.
Leftover Lunch: Advantage-based Offline Reinforcement Learning for Language Models
However, RLHF is an unstable and data-hungry process that continually requires new high-quality LM-generated data for finetuning.
Stanceosaurus: Classifying Stance Towards Multilingual Misinformation
We present Stanceosaurus, a new corpus of 28, 033 tweets in English, Hindi, and Arabic annotated with stance towards 251 misinformation claims.
Just Say No: Analyzing the Stance of Neural Dialogue Generation in Offensive Contexts
To better understand the dynamics of contextually offensive language, we investigate the stance of dialogue model responses in offensive Reddit conversations.
Extracting a Knowledge Base of COVID-19 Events from Social Media
In this paper, we present a manually annotated corpus of 10, 000 tweets containing public reports of five COVID-19 events, including positive and negative tests, deaths, denied access to testing, claimed cures and preventions.
Fluent Response Generation for Conversational Question Answering
In this work, we propose a method for situating QA responses within a SEQ2SEQ NLG approach to generate fluent grammatical answer responses while maintaining correctness.
Generating More Interesting Responses in Neural Conversation Models with Distributional Constraints
Neural conversation models tend to generate safe, generic responses for most inputs.
