Summary of Graph-based Uncertainty Metrics For Long-form Language Model Outputs, by Mingjian Jiang and Yangjun Ruan and Prasanna Sattigeri and Salim Roukos and Tatsunori Hashimoto
Graph-based Uncertainty Metrics for Long-form Language Model Outputs
by Mingjian Jiang, Yangjun Ruan, Prasanna Sattigeri, Salim Roukos, Tatsunori Hashimoto
First submitted to arxiv on: 28 Oct 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
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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 Graph Uncertainty, a novel method for estimating uncertainty in large language model (LLM) generations. The approach represents LLM outputs as bipartite graphs, linking claims to their supporting evidence. This allows for the use of graph centrality metrics to estimate claim-level uncertainty. The authors show that more advanced centrality measures, such as closeness centrality, outperform existing self-consistency-based methods. To further improve factuality, they introduce uncertainty-aware decoding techniques that leverage both graph structure and uncertainty estimates. Experimental results demonstrate significant gains in factuality (2-4%) and informativeness of generated responses. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps computers generate text more accurately by understanding which parts of the text are most likely to be true or false. Right now, these computer models can sometimes make up fake information that isn’t actually true. The authors have developed a new way to measure how uncertain their model is about certain claims it makes. This helps them focus on the most reliable parts of the text and avoid spreading misinformation. They’ve tested this approach and found it improves the accuracy and usefulness of the generated text. |
Keywords
» Artificial intelligence » Large language model
