2 citations · 4 across the 23 of their papers we have counts for
9 papers · 1 filter
Benchmarking and Improving Large Vision-Language Models for Fundamental Visual Graph Understanding and Reasoning
Yingjie Zhu, Xuefeng Bai, Kehai Chen +3
Large Vision-Language Models (LVLMs) have demonstrated remarkable performance across diverse tasks. Despite great success, recent studies show that LVLMs encounter substantial limi…
LinguaLIFT: An Effective Two-stage Instruction Tuning Framework for Low-Resource Language Reasoning
Hongbin Zhang, Kehai Chen, Xuefeng Bai +2
Large language models (LLMs) have exhibited impressive multilingual reasoning capabilities, driven by extensive multilingual pre-training corpora and instruction fine-tuning data.…
Beware of Calibration Data for Pruning Large Language Models
Yixin Ji, Yang Xiang, Juntao Li +5
As large language models (LLMs) are widely applied across various fields, model compression has become increasingly crucial for reducing costs and improving inference efficiency. P…
LLM-based Translation Inference with Iterative Bilingual Understanding
Andong Chen, Kehai Chen, Yang Xiang +5
The remarkable understanding and generation capabilities of large language models (LLMs) have greatly improved translation performance. However, incorrect understanding of the sent…
TF-Attack: Transferable and Fast Adversarial Attacks on Large Language Models
Zelin Li, Kehai Chen, Lemao Liu +4
With the great advancements in large language models (LLMs), adversarial attacks against LLMs have recently attracted increasing attention. We found that pre-existing adversarial a…
Large Language Models for Classical Chinese Poetry Translation: Benchmarking, Evaluating, and Improving
Andong Chen, Lianzhang Lou, Kehai Chen +5
Different from the traditional translation tasks, classical Chinese poetry translation requires both adequacy and fluency in translating culturally and historically significant con…
DUAL-REFLECT: Enhancing Large Language Models for Reflective Translation through Dual Learning Feedback Mechanisms
Andong Chen, Lianzhang Lou, Kehai Chen +5
Recently, large language models (LLMs) enhanced by self-reflection have achieved promising performance on machine translation. The key idea is guiding LLMs to generate translation…
Paying More Attention to Source Context: Mitigating Unfaithful Translations from Large Language Model
Hongbin Zhang, Kehai Chen, Xuefeng Bai +2
Large language models (LLMs) have showcased impressive multilingual machine translation ability. However, unlike encoder-decoder style models, decoder-only LLMs lack an explicit al…
Adaptive Feature-based Low-Rank Compression of Large Language Models via Bayesian Optimization
Yixin Ji, Yang Xiang, Juntao Li +6
In recent years, large language models (LLMs) have driven advances in natural language processing. Still, their growing scale has increased the computational burden, necessitating…