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- A contrastive neural disentanglement approach for query performance prediction
- Benchmarking prompt sensitivity in large language models
- Bias-Aware Curriculum Sampling For Fair Ranking
- Gender disentangled representation learning in neural rankers
- Enhanced retrieval effectiveness through selective query generation
- It Takes a Team to Triumph: Collaborative Expert Finding in Community QA Networks
- De-biasing relevance judgements for fair ranking
- Don't Raise Your Voice, Improve Your Argument: Learning to Retrieve Convincing Arguments
- Embedding-based team formation for community question answering
- Learning query-space document representations for high-recall retrieval
- Neural disentanglement of query difficulty and semantics
- TEAM DISCOVERY FOR COMMUNITY-BASED QUESTION ANSWERING SYSTEMS
- A Light-Weight Strategy for Restraining Gender Biases in Neural Rankers
- A Light-Weight Strategy for Restraining Gender Biases in Neural Rankers
- A Neural Approach to Forming Coherent Teams in Collaboration Networks
- A Neural Approach to Forming Coherent Teams in Collaboration Networks
- Addressing gender-related performance disparities in neural rankers
- Bias-aware Fair Neural Ranking for Addressing Stereotypical Gender Biases
- Feature-based question routing in community question answering platforms
- Gender fairness in information retrieval systems
- Collaborative experts discovery in social coding platforms
- Collaborative experts discovery in social coding platforms
- Exploring Gender Biases in Information Retrieval Relevance Judgement Datasets
- Matches made in heaven: Toolkit and large-scale datasets for supervised query reformulation
- On the orthogonality of bias and utility in ad hoc retrieval
- OpenAttHetRL: An Open Source Toolkit for Attributed Heterogeneous Network Representation Learning
- Query Performance Prediction Through Retrieval Coherency