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cs.LG2024
Scalable Ensemble Diversification for OOD Generalization and Detection
Alexander Rubinstein, Luca Scimeca, Damien Teney +1
Training a diverse ensemble of models has several practical applications such as providing candidates for model selection with better out-of-distribution (OOD) generalization, and…
cs.HC2024
Towards User-Focused Research in Training Data Attribution for Human-Centered Explainable AI
Elisa Nguyen, Johannes Bertram, Evgenii Kortukov +2
Explainable AI (XAI) aims to make AI systems more transparent, yet many practices emphasise mathematical rigour over practical user needs. We propose an alternative to this model-c…
cs.LG2024
Studying Large Language Model Behaviors Under Context-Memory Conflicts With Real Documents
Evgenii Kortukov, Alexander Rubinstein, Elisa Nguyen +1
Retrieval-augmented generation (RAG) mitigates many problems of fully parametric language models, such as temporal degradation, hallucinations, and lack of grounding. In RAG, the m…