5 citations · 7 across the 6 of their papers we have counts for
6 papers
V-SEAM: Visual Semantic Editing and Attention Modulating for Causal Interpretability of Vision-Language Models
Qidong Wang, Junjie Hu, Ming Jiang
Recent advances in causal interpretability have extended from language models to vision-language models (VLMs), seeking to reveal their internal mechanisms through input interventi…
Large Language Models Are Active Critics in NLG Evaluation
Shuying Xu, Junjie Hu, Ming Jiang
The conventional paradigm of using large language models (LLMs) for natural language generation (NLG) evaluation relies on pre-defined task definitions and evaluation criteria, pos…
How Well Do LLMs Identify Cultural Unity in Diversity?
Jialin Li, Junli Wang, Junjie Hu +1
Much work on the cultural awareness of large language models (LLMs) focuses on the models' sensitivity to geo-cultural diversity. However, in addition to cross-cultural differences…
Lookahead Exploration with Neural Radiance Representation for Continuous Vision-Language Navigation
Zihan Wang, Xiangyang Li, Jiahao Yang +4
Vision-and-language navigation (VLN) enables the agent to navigate to a remote location following the natural language instruction in 3D environments. At each navigation step, the…
Prompting Large Vision-Language Models for Compositional Reasoning
Timothy Ossowski, Ming Jiang, Junjie Hu
Vision-language models such as CLIP have shown impressive capabilities in encoding texts and images into aligned embeddings, enabling the retrieval of multimodal data in a shared e…
CFBenchmark: Chinese Financial Assistant Benchmark for Large Language Model
Yang Lei, Jiangtong Li, Dawei Cheng +2
Large language models (LLMs) have demonstrated great potential in the financial domain. Thus, it becomes important to assess the performance of LLMs in the financial tasks. In this…