most citedMAPO: Boosting Large Language Model Performance with Model-Adaptive Prompt Optimization

2 citations · 7 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CL2024

Evaluating Semantic Variation in Text-to-Image Synthesis: A Causal Perspective

Xiangru Zhu, Penglei Sun, Yaoxian Song +6

Accurate interpretation and visualization of human instructions are crucial for text-to-image (T2I) synthesis. However, current models struggle to capture semantic variations from…

cs.CL2024★ 2 cited

MAPO: Boosting Large Language Model Performance with Model-Adaptive Prompt Optimization

Yuyan Chen, Zhihao Wen, Ge Fan +6

Prompt engineering, as an efficient and effective way to leverage Large Language Models (LLM), has drawn a lot of attention from the research community. The existing research prima…

cs.CV2024

XMeCap: Meme Caption Generation with Sub-Image Adaptability

Yuyan Chen, Songzhou Yan, Zhihong Zhu +2

Humor, deeply rooted in societal meanings and cultural details, poses a unique challenge for machines. While advances have been made in natural language processing, real-world humo…

cs.CL2024★ 1 cited

ESC-Eval: Evaluating Emotion Support Conversations in Large Language Models

Haiquan Zhao, Lingyu Li, Shisong Chen +11

Emotion Support Conversation (ESC) is a crucial application, which aims to reduce human stress, offer emotional guidance, and ultimately enhance human mental and physical well-bein…

cs.CL2024★ 1 cited

OVEL: Large Language Model as Memory Manager for Online Video Entity Linking

Haiquan Zhao, Xuwu Wang, Shisong Chen +3

In recent years, multi-modal entity linking (MEL) has garnered increasing attention in the research community due to its significance in numerous multi-modal applications. Video, a…

cs.CV2023★ 1 cited

A Contrastive Compositional Benchmark for Text-to-Image Synthesis: A Study with Unified Text-to-Image Fidelity Metrics

Xiangru Zhu, Penglei Sun, Chengyu Wang +4

Text-to-image (T2I) synthesis has recently achieved significant advancements. However, challenges remain in the model's compositionality, which is the ability to create new combina…

cs.AI2023★ 2 cited

M^2ConceptBase: A Fine-Grained Aligned Concept-Centric Multimodal Knowledge Base

Zhiwei Zha, Jiaan Wang, Zhixu Li +3

Multimodal knowledge bases (MMKBs) provide cross-modal aligned knowledge crucial for multimodal tasks. However, the images in existing MMKBs are generally collected for entities in…

cs.AI2023

Scene-Driven Multimodal Knowledge Graph Construction for Embodied AI

Song Yaoxian, Sun Penglei, Liu Haoyu +4

Embodied AI is one of the most popular studies in artificial intelligence and robotics, which can effectively improve the intelligence of real-world agents (i.e. robots) serving hu…