4 papers
Mask-to-Correct: Leveraging Retriever Diversity for Masking-guided Faithful Fact Correction
Payel Santra, Lavisha Sharma, Madhusudan Ghosh +1
The rapid spread of misinformation on social media highlights the need for robust, automated fact correction frameworks. However, existing works rely on supervised learning from ma…
Breaking Flat: A Generalised Query Performance Prediction Evaluation Framework
Payel Santra, Partha Basuchowdhuri, Debasis Ganguly
The traditional use-case of query performance prediction (QPP) is to identify which queries perform well and which perform poorly for a given ranking model. A more fine-grained and…
Beyond Correlations: A Downstream Evaluation Framework for Query Performance Prediction
Payel Santra, Partha Basuchowdhuri, Debasis Ganguly
The standard practice of query performance prediction (QPP) evaluation is to measure a set-level correlation between the estimated retrieval qualities and the true ones. However, n…
HF-RAG: Hierarchical Fusion-based RAG with Multiple Sources and Rankers
Payel Santra, Madhusudan Ghosh, Debasis Ganguly +2
Leveraging both labeled (input-output associations) and unlabeled data (wider contextual grounding) may provide complementary benefits in retrieval augmented generation (RAG). Howe…