1 citations · 3 across the 9 of their papers we have counts for
9 papers
VisualActBench: Can VLMs See and Act like a Human?
Daoan Zhang, Pai Liu, Xiaofei Zhou +6
Vision-Language Models (VLMs) have achieved impressive progress in perceiving and describing visual environments. However, their ability to proactively reason and act based solely…
NP-LoRA: Null Space Projection for Subject-Style LoRA Fusion
Chuheng Chen, Xiaofei Zhou, Geyuan Zhang +1
Low-Rank Adaptation (LoRA) fusion enables the composition of subject and style representations for controllable generation without retraining. However, existing approaches primaril…
LaRe: Latent Refocusing for Multimodal Reasoning
Jizheng Ma, Xiaofei Zhou, Geyuan Zhang +2
Chain of Thought (CoT) reasoning enhances logical performance by decomposing complex tasks, yet its multimodal extension faces a trade-off. The prevailing Thinking with Images para…
AICrypto: Evaluating Cryptography Capabilities of Large Language Models
Yu Wang, Yijian Liu, Liheng Ji +11
We build \textbf{AICrypto}, a comprehensive benchmark designed to evaluate the cryptography capabilities of large language models (LLMs). The benchmark comprises 135 multiple-choic…
Why Reasoning Matters? A Survey of Advancements in Multimodal Reasoning (v1)
Jing Bi, Susan Liang, Xiaofei Zhou +16
Reasoning is central to human intelligence, enabling structured problem-solving across diverse tasks. Recent advances in large language models (LLMs) have greatly enhanced their re…
Jailbreak Large Vision-Language Models Through Multi-Modal Linkage
Yu Wang, Xiaofei Zhou, Yichen Wang +2
With the significant advancement of Large Vision-Language Models (VLMs), concerns about their potential misuse and abuse have grown rapidly. Previous studies have highlighted VLMs'…
HUT: A More Computation Efficient Fine-Tuning Method With Hadamard Updated Transformation
Geyuan Zhang, Xiaofei Zhou, Chuheng Chen
Fine-tuning pre-trained language models for downstream tasks has achieved impressive results in NLP. However, fine-tuning all parameters becomes impractical due to the rapidly incr…
Exploring Explicit and Implicit Visual Relationships for Image Captioning
Zeliang Song, Xiaofei Zhou
Image captioning is one of the most challenging tasks in AI, which aims to automatically generate textual sentences for an image. Recent methods for image captioning follow encoder…
Improving Abstractive Text Summarization with History Aggregation
Pengcheng Liao, Chuang Zhang, Xiaojun Chen +1
Recent neural sequence to sequence models have provided feasible solutions for abstractive summarization. However, such models are still hard to tackle long text dependency in the…