Papers by Andrew Blair-Stanek
CLERC: A Dataset for U. S. Legal Case Retrieval and Retrieval-Augmented Analysis Generation (2025.findings-naacl)
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Abe Bohan Hou, Orion Weller, Guanghui Qin, Eugene Yang, Dawn Lawrie, Nils Holzenberger, Andrew Blair-Stanek, Benjamin Van Durme
| Challenge: | a dataset of case law is used to train and evaluate models for writing legal analyses . current approaches struggle to find relevant cases and generate legal analyses, authors say . |
| Approach: | They build a dataset of case law to support information retrieval and retrieval-augmented generation. |
| Outcome: | The proposed dataset supports two important backbone tasks: retrieval (IR) and retrieval-augmented generation (RAG). |
ADAPTIVE IE: Investigating the Complementarity of Human-AI Collaboration to Adaptively Extract Information on-the-fly (2025.coling-main)
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Ishani Mondal, Michelle Yuan, Anandhavelu N, Aparna Garimella, Francis Ferraro, Andrew Blair-Stanek, Benjamin Van Durme, Jordan Boyd-Graber
| Challenge: | Existing IE systems are either fully supervised, requiring expensive human annotations, or fully unsupervised, extracting information that often do not cater to user’s needs. |
| Approach: | They propose a framework that uses human-in-the-loop refinement to adapt to changing user questions. |
| Outcome: | The proposed framework is domain-agnostic, responsive, efficient for helping users access useful information while quickly reorganizing information in response to evolving information needs. |