1 citations · 1 across the 17 of their papers we have counts for
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Scaling Multilingual Mixture-of-Experts: How Language Coverage Changes Capacity and Compute Allocation
Joel Dag, Nikit Srivastava, Hamada M. Zahera +1
Multilingual models share capacity across languages, so adding languages can hurt performance on existing ones. Mixture-of-experts models expand this capacity with little additiona…
MARS: Multi-hop Adaptive Retrieval and SPARQL Generation for KGQA
Nikit Srivastava, Daniel Vollmers, René Speck +3
Large language models (LLMs) have demonstrated strong reasoning performance, but their tendency to hallucinate limits their reliability in knowledge-intensive tasks requiring up-to…
Benchmarking Knowledge Editing using Logical Rules
Tatiana Moteu Ngoli, NDah Jean Kouagou, Hamada M. Zahera +1
Large Language Models (LLMs) are increasingly deployed in real-world applications that require access to up-to-date knowledge. However, retraining LLMs is computationally expensive…
Learning Chain Of Thoughts Prompts for Predicting Entities, Relations, and even Literals on Knowledge Graphs
Alkid Baci, Luke Friedrichs, Caglar Demir +2
Knowledge graph embedding (KGE) models perform well on link prediction but struggle with unseen entities, relations, and especially literals, limiting their use in dynamic, heterog…