Paper-Conference

When Attention Becomes Exposure in Generative Search
Examining how attention mechanisms in generative search affect information exposure.
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.
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.
Say the Task, Build the Team: Prompt-Based Team Formation
Prompt-based team formation using natural language task descriptions.
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.
De-biasing relevance judgements for fair ranking
Methods for de-biasing relevance judgements for fair ranking.