Papers by Sheridan Feucht
Token Erasure as a Footprint of Implicit Vocabulary Items in LLMs (2024.emnlp-main)
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| Challenge: | Current language models process text as sequences of tokens that roughly correspond to words . individual tokens are often semantically unrelated to the meanings of the words/concepts they comprise . |
| Approach: | They propose a method to "read out" the implicit vocabulary of an autoregressive LLM by examining differences in token representations across layers. |
| Outcome: | The proposed method "reads out" the implicit vocabulary of an autoregressive LLM by examining differences in token representations across layers. |
NEWTS: A Corpus for News Topic-Focused Summarization (2022.findings-acl)
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| Challenge: | Existing benchmarking corpora provide concordant pairs of full and abridged versions of Web, news or professional content. |
| Approach: | They propose a topical summarization corpus called NEWTS that is annotated via crowd-sourcing. |
| Outcome: | The proposed model can condition summaries on a desired range of themes . the proposed model outperforms Lead-3 baselines on most benchmark datasets . |