Summary of Lfosum: Summarizing Long-form Opinions with Large Language Models, by Mir Tafseer Nayeem et al.
LFOSum: Summarizing Long-form Opinions with Large Language Models
by Mir Tafseer Nayeem, Davood Rafiei
First submitted to arxiv on: 16 Oct 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Emerging Technologies (cs.ET); Human-Computer Interaction (cs.HC); Information Retrieval (cs.IR)
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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 addresses the issue of online reviews overwhelming consumers by introducing a new dataset of user reviews and two Large Language Model (LLM) based summarization approaches that can handle long inputs. The dataset consists of over 1,000 reviews for each entity, paired with in-depth summaries from domain experts to serve as a reference for evaluation. The paper also proposes automatic evaluation metrics to assess the faithfulness of summaries. Various open-source and closed-source LLMs are benchmarked using these methods, revealing that while they still struggle to balance sentiment and format adherence in long-form summaries, open-source models can improve when focusing on relevant information. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps solve a big problem: how to make sense of lots of online reviews. Reviews can be super helpful, but there are so many of them that it’s hard to figure out what’s important. The researchers created a new way to summarize reviews using special language models. They also made a new dataset with thousands of reviews for each thing, and used expert summaries as a reference to check how well the models worked. They even came up with new ways to measure how good the summaries are. By testing different language models, they found that some do better than others at making sense of long reviews. |
Keywords
» Artificial intelligence » Large language model » Summarization
