1 citations · 1 across the 5 of their papers we have counts for
5 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…
ExPosST: Explicit Positioning with Adaptive Masking for LLM-Based Simultaneous Machine Translation
Yuzhe Shang, Pengzhi Gao, Yazheng Yang +4
Large language models (LLMs) have recently demonstrated promising performance in simultaneous machine translation (SimulMT). However, applying decoder-only LLMs to SimulMT introduc…
Detecting Contextual Hallucinations in LLMs with Frequency-Aware Attention
Siya Qi, Yudong Chen, Runcong Zhao +6
Hallucination detection is critical for ensuring the reliability of large language models (LLMs) in context-based generation. Prior work has explored intrinsic signals available du…
How Reliable is Multilingual LLM-as-a-Judge?
Xiyan Fu, Wei Liu
LLM-as-a-Judge has emerged as a popular evaluation strategy, where advanced large language models assess generation results in alignment with human instructions. While these models…
Aligning Black-box Language Models with Human Judgments
Gerrit J. J. van den Burg, Gen Suzuki, Wei Liu +1
Large language models (LLMs) are increasingly used as automated judges to evaluate recommendation systems, search engines, and other subjective tasks, where relying on human evalua…