Information Retrieval

Self-Paced Fair Ranking with Loss as a Proxy for Bias
Self-paced fair ranking using loss as a proxy for bias.
A contrastive neural disentanglement approach for query performance prediction
Contrastive neural disentanglement approach for query performance prediction.
Benchmarking prompt sensitivity in large language models
Benchmarking prompt sensitivity in large language models.
Bias-Aware Curriculum Sampling For Fair Ranking
Bias-aware curriculum sampling for fair ranking.
Datasets for Supervised Adversarial Attacks on Neural Rankers
Datasets for supervised adversarial attacks on neural rankers.
Gender disentangled representation learning in neural rankers
Gender disentangled representation learning in neural rankers for bias mitigation.
LLM-as-a-Judge in Entity Retrieval: Assessing Explicit and Implicit Relevance
Using LLMs as judges for assessing explicit and implicit relevance in entity retrieval.
Who Gets to be an Expert? The Hidden Bias in Expert Finding
Investigating hidden biases in expert finding systems.
Enhanced retrieval effectiveness through selective query generation
Enhanced retrieval effectiveness through selective query generation.
It Takes a Team to Triumph: Collaborative Expert Finding in Community QA Networks
Collaborative expert finding in community QA networks.