Papers by Jason Hoelscher-Obermaier
Detecting Edit Failures In Large Language Models: An Improved Specificity Benchmark (2023.findings-acl)
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| Challenge: | Recent model editing techniques can introduce large unwanted side effects, a new study shows . existing specificity benchmarks do not detect these unwanted side-effects . a recent study shows that model edits can cause significant performance drop . |
| Approach: | They extend existing CounterFact benchmark to include a dynamic component and propose a new benchmark to evaluate model editing techniques. |
| Outcome: | The proposed benchmark improves existing benchmarks for specificity and avoids unwanted side effects. |