Search Results for author:
Found 8 papers, 4 papers with code
Conversation-Aware Filtering of Online Patient Forum Messages
We experiment with two approaches to add conversational context to a BERT model: a sequential CRF layer and manually engineered features.
FuzzyBIO: A Proposal for Fuzzy Representation of Discontinuous Entities
Using FuzzyBIO also improves end-to-end performance for continuous and composite entities in two of three data sets.
Retrieval for Extremely Long Queries and Documents with RPRS: a Highly Efficient and Effective Transformer-based Re-Ranker
Furthermore, our method solves the problem of the low-resource training in QBD retrieval tasks as it does not need large amounts of training data, and has only three parameters with a limited range that can be optimized with a grid search even if a small amount of labeled data is available.
Injecting the BM25 Score as Text Improves BERT-Based Re-rankers
In this paper we propose a novel approach for combining first-stage lexical retrieval models and Transformer-based re-rankers: we inject the relevance score of the lexical model as a token in the middle of the input of the cross-encoder re-ranker.
Breaking BERT: Understanding its Vulnerabilities for Named Entity Recognition through Adversarial Attack
Experimental results show that BERT models are vulnerable to variation in the entity context with 20. 2 to 45. 0% of entities predicted completely wrong and another 29. 3 to 53. 3% of entities predicted wrong partially.
TRECVID 2020: A comprehensive campaign for evaluating video retrieval tasks across multiple application domains
In total, 29 teams from various research organizations worldwide completed one or more of the following six tasks: 1.
TRECVID 2019: An Evaluation Campaign to Benchmark Video Activity Detection, Video Captioning and Matching, and Video Search & Retrieval
The TREC Video Retrieval Evaluation (TRECVID) 2019 was a TREC-style video analysis and retrieval evaluation, the goal of which remains to promote progress in research and development of content-based exploitation and retrieval of information from digital video via open, metrics-based evaluation.
Lexical Normalization of User-Generated Medical Text
In the medical domain, user-generated social media text is increasingly used as a valuable complementary knowledge source to scientific medical literature.
