14 citations · 42 across the 22 of their papers we have counts for
8 papers · 1 filter
PunchBench: Benchmarking MLLMs in Multimodal Punchline Comprehension
Kun Ouyang, Yuanxin Liu, Shicheng Li +5
Multimodal punchlines, which involve humor or sarcasm conveyed in image-caption pairs, are a popular way of communication on online multimedia platforms. With the rapid development…
Temporal Reasoning Transfer from Text to Video
Lei Li, Yuanxin Liu, Linli Yao +6
Video Large Language Models (Video LLMs) have shown promising capabilities in video comprehension, yet they struggle with tracking temporal changes and reasoning about temporal rel…
Auxiliary-Loss-Free Load Balancing Strategy for Mixture-of-Experts
Lean Wang, Huazuo Gao, Chenggang Zhao +2
For Mixture-of-Experts (MoE) models, an unbalanced expert load will lead to routing collapse or increased computational overhead. Existing methods commonly employ an auxiliary loss…
DeCo: Decoupling Token Compression from Semantic Abstraction in Multimodal Large Language Models
Linli Yao, Lei Li, Shuhuai Ren +4
The visual projector, which bridges the vision and language modalities and facilitates cross-modal alignment, serves as a crucial component in MLLMs. However, measuring the effecti…
Modal-adaptive Knowledge-enhanced Graph-based Financial Prediction from Monetary Policy Conference Calls with LLM
Kun Ouyang, Yi Liu, Shicheng Li +3
Financial prediction from Monetary Policy Conference (MPC) calls is a new yet challenging task, which targets at predicting the price movement and volatility for specific financial…
LaDiC: Are Diffusion Models Really Inferior to Autoregressive Counterparts for Image-to-Text Generation?
Yuchi Wang, Shuhuai Ren, Rundong Gao +5
Diffusion models have exhibited remarkable capabilities in text-to-image generation. However, their performance in image-to-text generation, specifically image captioning, has lagg…
Towards Multimodal Video Paragraph Captioning Models Robust to Missing Modality
Sishuo Chen, Lei Li, Shuhuai Ren +5
Video paragraph captioning (VPC) involves generating detailed narratives for long videos, utilizing supportive modalities such as speech and event boundaries. However, the existing…
TempCompass: Do Video LLMs Really Understand Videos?
Yuanxin Liu, Shicheng Li, Yi Liu +6
Recently, there is a surge in interest surrounding video large language models (Video LLMs). However, existing benchmarks fail to provide a comprehensive feedback on the temporal p…