11 citations · 24 across the 10 of their papers we have counts for
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cs.CL2024★ 1 cited
Pointwise Mutual Information as a Performance Gauge for Retrieval-Augmented Generation
Tianyu Liu, Jirui Qi, Paul He +3
Recent work suggests that large language models enhanced with retrieval-augmented generation are easily influenced by the order, in which the retrieved documents are presented to t…
cs.CL2024★ 2 cited
The SIFo Benchmark: Investigating the Sequential Instruction Following Ability of Large Language Models
Xinyi Chen, Baohao Liao, Jirui Qi +4
Following multiple instructions is a crucial ability for large language models (LLMs). Evaluating this ability comes with significant challenges: (i) limited coherence between mult…
cs.CL2024★ 8 cited
Model Internals-based Answer Attribution for Trustworthy Retrieval-Augmented Generation
Jirui Qi, Gabriele Sarti, Raquel Fernández +1
Ensuring the verifiability of model answers is a fundamental challenge for retrieval-augmented generation (RAG) in the question answering (QA) domain. Recently, self-citation promp…