References

Following sets of papers and articles have inspired our current and upcoming build of HapticAI

• WebGPT: Browser-assisted question-answering with human feedback (OpenAI, 2021):

• ChatGPT: Optimizing Language Models for Dialogue (OpenAI 2022)

• Learning to summarize with human feedback (Stiennon et al., 2020)

• Recursively Summarizing Books with Human Feedback (OpenAI Alignment Team 2021)

• Llama 2 (Touvron et al. 2023)

• Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback (Anthropic, 2022)

• Fine-Tuning Language Models from Human Preferences (Zieglar et al. 2019)

• InstructGPT: Training language models to follow instructions with human feedback (OpenAI Alignment Team 2022)

• GopherCite: Teaching language models to support answers with verified quotes (Menick et al. 2022)

• Sparrow: Improving alignment of dialogue agents via targeted human judgements (Glaese et al. 2022)

• Dynamic Planning in Open-Ended Dialogue using Reinforcement Learning (Cohen at al. 2022)

• Is Reinforcement Learning (Not) for Natural Language Processing?: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization (Ramamurthy and Ammanabrolu et al. 2022)