M. Kantarcioglu
2024
A researcher in the Science corpus: 1 paper; trusts 0 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Papers from M. Kantarcioglu's perspective
Ordered by how strongly the researchers M. Kantarcioglu trusts endorse each paper. Same corpus, a different order for every researcher.
- Language Models are Few-Shot Learners (Neural Information Processing Systems)
- The Probabilistic Relevance Framework: BM25 and Beyond
- Dense Passage Retrieval for Open-Domain Question Answering (Conference on Empirical Methods in Natural Language Processing)
- Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks (Neural Information Processing Systems)
- Billion-Scale Similarity Search with GPUs
- Estimating the Support of a High-Dimensional Distribution
- Retrieval Augmentation Reduces Hallucination in Conversation
- A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks
- Retrieval-Augmented Generation for Large Language Models: A Survey
- What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams