Papers by Leslie Barrett
LexTime: A Benchmark for Temporal Ordering of Legal Events (2025.findings-emnlp)
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| Challenge: | Existing benchmarks lack specialized language evaluation for LLMs on event ordering in legal contexts. |
| Approach: | They propose to use a dataset to evaluate LLMs' event ordering capabilities in legal language to evaluate their temporal relations with legal events. |
| Outcome: | The proposed model improves on a dataset of 512 instances from U.S. Federal Complaints with annotated event pairs and their temporal relations. |
Can LLMs Be Efficient Predictors of Conversational Derailment? (2025.findings-emnlp)
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| Challenge: | Conversational derailment is a common issue on online platforms due to toxic or inappropriate remarks. |
| Approach: | They prompt pre-trained large language models to predict conversational derailment without fine-tuning . they compare chain-of-thought reasoning and few-shot exemplars to predict derailments . |
| Outcome: | The proposed model predicts conversational derailment without task-specific fine-tuning without fine-cuning. |
Can LLMs Find a Needle in a Haystack? A Look at Anomaly Detection Language Modeling (2025.findings-emnlp)
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| Challenge: | Anomaly detection (AD) is a problem in machine learning, but it is not always competitive on certain datasets. |
| Approach: | They propose a new approach to Anomaly detection based on large pre-trained language models in three modalities. |
| Outcome: | The proposed model beats baselines on anomaly detection when presented as imbalanced classification problem regardless of the concentration of anomalous samples. |