Summary of On the Limits Of Language Generation: Trade-offs Between Hallucination and Mode Collapse, by Alkis Kalavasis et al.
On the Limits of Language Generation: Trade-Offs Between Hallucination and Mode Collapse
by Alkis Kalavasis, Anay Mehrotra, Grigoris Velegkas
First submitted to arxiv on: 14 Nov 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Data Structures and Algorithms (cs.DS); 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 The paper investigates the fundamental properties required of a language model, focusing on two crucial aspects: generating novel, valid strings not seen during training and capturing the richness of an unknown language. The authors highlight the importance of avoiding “hallucination” (producing invalid strings) and “mode collapse” (failing to capture the full range). They pose the question: Can a language model simultaneously meet these two essential requirements? The paper explores this challenge, shedding light on the difficulties in specifying desirable properties for language models. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine trying to teach a computer to understand and generate text from a new language. This is like learning a new language yourself! But what if the computer starts producing nonsense words or only knows how to say simple things? The researchers are trying to figure out how to make sure the computer can both create new, correct sentences and express itself well in this new language. They want to know if it’s possible for the computer to do both of these things at the same time. |
Keywords
* Artificial intelligence * Hallucination * Language model
