7 citations · 7 across the 6 of their papers we have counts for
6 papers
LNE-Blocking: An Efficient Framework for Contamination Mitigation Evaluation on Large Language Models
Ruijie Hou, Yueyang Jiao, Hanxu Hu +4
The problem of data contamination is now almost inevitable during the development of large language models (LLMs), with the training data commonly integrating those evaluation benc…
Lost in Literalism: How Supervised Training Shapes Translationese in LLMs
Yafu Li, Ronghao Zhang, Zhilin Wang +5
Large language models (LLMs) have achieved remarkable success in machine translation, demonstrating impressive performance across diverse languages. However, translationese, charac…
Reasoning is All You Need for Video Generalization: A Counterfactual Benchmark with Sub-question Evaluation
Qiji Zhou, Yifan Gong, Guangsheng Bao +5
Counterfactual reasoning is crucial for robust video understanding but remains underexplored in existing multimodal benchmarks. In this paper, we introduce \textbf{COVER} (\textbf{…
What Have We Achieved on Non-autoregressive Translation?
Yafu Li, Huajian Zhang, Jianhao Yan +2
Recent advances have made non-autoregressive (NAT) translation comparable to autoregressive methods (AT). However, their evaluation using BLEU has been shown to weakly correlate wi…
Revisiting Cross-Lingual Summarization: A Corpus-based Study and A New Benchmark with Improved Annotation
Yulong Chen, Huajian Zhang, Yijie Zhou +8
Most existing cross-lingual summarization (CLS) work constructs CLS corpora by simply and directly translating pre-annotated summaries from one language to another, which can conta…
Chain-of-Symbol Prompting Elicits Planning in Large Langauge Models
Hanxu Hu, Hongyuan Lu, Huajian Zhang +3
In this paper, we take the initiative to investigate the performance of LLMs on complex planning tasks that require LLMs to understand a virtual spatial environment simulated via n…