11 citations · 24 across the 10 of their papers we have counts for
10 papers
Last Translation Benchmark
Vilém Zouhar, Niyati Bafna, Mukund Choudhary +263
For scientific progress, we need benchmarks that test the limits of state-of-the-art models, and evaluation methods that inform us about failure cases. As models get stronger, stan…
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…
How role-play shapes relevance judgment in zero-shot LLM rankers
Yumeng Wang, Jirui Qi, Catherine Chen +2
Large Language Models (LLMs) have emerged as promising zero-shot rankers, but their performance is highly sensitive to prompt formulation. In particular, role-play prompts, where t…
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…
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…
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…
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…
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…
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…
Cross Domain Few-Shot Learning via Meta Adversarial Training
Jirui Qi, Richong Zhang, Chune Li +1
Few-shot relation classification (RC) is one of the critical problems in machine learning. Current research merely focuses on the set-ups that both training and testing are from th…