Papers by Ted Briscoe
Neural Automated Essay Scoring and Coherence Modeling for Adversarially Crafted Input (N18-1)
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| Challenge: | Existing approaches to Automated Essay Scoring (AES) are not well-suited to capture adversarially crafted input of grammatical but incoherent sequences of sentences. |
| Approach: | They propose a neural model of local coherence that can effectively learn connectedness features between sentences. |
| Outcome: | The proposed approach strengthens the validity of neural essay scoring models. |
PeerQA: A Scientific Question Answering Dataset from Peer Reviews (2025.naacl-long)
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| Challenge: | a dataset of 579 QA pairs from 208 scientific articles contains answers that reviewers raised while thoroughly examining the scientific article. |
| Approach: | They propose a dataset that contains questions that reviewers raised while thoroughly examining the scientific article. |
| Outcome: | The proposed dataset contains 579 QA pairs from 208 academic articles . the results show that decontextualization approaches improve retrieval performance . |
The Good, the Bad and the Constructive: Automatically Measuring Peer Review’s Utility for Authors (2025.emnlp-main)
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| Challenge: | Providing constructive feedback to authors is a core component of peer review . authors lack guidance on how to improve their review, a problem that is often overlooked . |
| Approach: | They use a RevUtil dataset to benchmark fine-tuned models for assessing review comments . they find that machine-generated reviews generally underperform human reviews on these aspects . |
| Outcome: | The proposed model outperforms closed models on four aspects of review comments . the proposed model achieves agreement levels comparable to and exceeding those of human models . |
Which Word Orders Facilitate Length Generalization in LMs? An Investigation with GCG-Based Artificial Languages (2025.emnlp-main)
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| Challenge: | Whether language models have inductive biases favoring typologically frequent grammatical properties over rare, implausible ones has been investigated, typically using artificial languages (ALs). |
| Approach: | They extend their context-free AL formalization by adopting Generalized Categorial Grammar (GCG) . they also examine the generalization ability of LMs to process unseen longer test sentences . |
| Outcome: | The proposed models better capture features of natural languages and can process unseen longer test sentences. |
Automatic learner summary assessment for reading comprehension (N19-1)
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| Challenge: | Summarization is a well-established method of measuring reading proficiency in traditional English as a second or other language assessments. |
| Approach: | They propose three approaches to automatically assess learner summary for evaluating non-native reading comprehension using a summarization task and a long-term memory model. |
| Outcome: | The proposed models outperform traditional methods and produce quality assessments close to professional examiners. |