Summary of Linguistic Calibration Of Long-form Generations, by Neil Band and Xuechen Li and Tengyu Ma and Tatsunori Hashimoto
Linguistic Calibration of Long-Form Generations
by Neil Band, Xuechen Li, Tengyu Ma, Tatsunori Hashimoto
First submitted to arxiv on: 30 Mar 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Machine Learning (stat.ML)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper proposes a novel approach to mitigate the issue of language models (LMs) confidently hallucinating and leading users to make suboptimal decisions. The authors introduce linguistic calibration, where an LM produces long-form text with confidence statements, enabling users to make calibrated probabilistic predictions. A training framework is developed, comprising a supervised finetuning step and a reinforcement learning step that rewards generations with confidence statements. The proposed approach is tested on the Llama 2 7B model, demonstrating significant calibration improvements over strong factuality baselines. The results generalize well across various domains, including scientific and biomedical questions, and a person biography generation task. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper tries to fix a problem with language models (LMs) that can sometimes make mistakes by confidently saying something is true when it’s not. This can lead people to make bad decisions. The authors want to help LMs provide more accurate information by having them say how sure they are of what they’re saying. For example, an LM might say “I think there’s a 30% chance that…” or “I’m certain that…”. They test their idea on a language model called Llama and find it works well. The results apply to different areas like science and medicine, as well as writing biographies about people. |
Keywords
» Artificial intelligence » Language model » Llama » Reinforcement learning » Supervised
