2 citations · 2 across the 3 of their papers we have counts for
7 papers · 1 filter
Post-Training Language Models for Crosslingual Consistency
Tianyu Liu, Jirui Qi, Mrinmaya Sachan +3
Language models often respond inconsistently to translation-equivalent prompts across languages, undermining the reliability of multilingual systems. To quantify this, we give an i…
On the Consistency of Multilingual Context Utilization in Retrieval-Augmented Generation
Jirui Qi, Raquel Fernández, Arianna Bisazza
Retrieval-augmented generation (RAG) with large language models (LLMs) has demonstrated strong performance in multilingual question-answering (QA) tasks by leveraging relevant pass…
When Models Reason in Your Language: Controlling Thinking Language Comes at the Cost of Accuracy
Jirui Qi, Shan Chen, Zidi Xiong +3
Recent Large Reasoning Models (LRMs) with thinking traces have shown strong performance on English reasoning tasks. However, their ability to think in other languages is less studi…
Cross-Lingual Consistency of Factual Knowledge in Multilingual Language Models
Jirui Qi, Raquel Fernández, Arianna Bisazza
Multilingual large-scale Pretrained Language Models (PLMs) have been shown to store considerable amounts of factual knowledge, but large variations are observed across languages. W…
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…
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…