6 papers
Beyond Training for Cultural Awareness: The Role of Dataset Linguistic Structure in Large Language Models
Reem I. Masoud, Chen Feng, Shunta Asano +3
The global deployment of large language models (LLMs) has raised concerns about cultural misalignment, yet the linguistic properties of fine-tuning datasets used for cultural adapt…
Noisy but Valid: Robust Statistical Evaluation of LLMs with Imperfect Judges
Chen Feng, Minghe Shen, Ananth Balashankar +2
Reliable certification of Large Language Models (LLMs)-verifying that failure rates are below a safety threshold-is critical yet challenging. While "LLM-as-a-Judge" offers scalabil…
Seedance 1.5 pro: A Native Audio-Visual Joint Generation Foundation Model
Team Seedance, Heyi Chen, Siyan Chen +194
Recent strides in video generation have paved the way for unified audio-visual generation. In this work, we present Seedance 1.5 pro, a foundational model engineered specifically f…
Qianfan-VL: Domain-Enhanced Universal Vision-Language Models
Daxiang Dong, Mingming Zheng, Dong Xu +32
We present Qianfan-VL, a series of multimodal large language models ranging from 3B to 70B parameters, achieving state-of-the-art performance through innovative domain enhancement…
Seeing and Reasoning with Confidence: Supercharging Multimodal LLMs with an Uncertainty-Aware Agentic Framework
Zhuo Zhi, Chen Feng, Adam Daneshmend +6
Multimodal large language models (MLLMs) show promise in tasks like visual question answering (VQA) but still face challenges in multimodal reasoning. Recent works adapt agentic fr…
PROSAC: Provably Safe Certification for Machine Learning Models under Adversarial Attacks
Chen Feng, Ziquan Liu, Zhuo Zhi +3
It is widely known that state-of-the-art machine learning models, including vision and language models, can be seriously compromised by adversarial perturbations. It is therefore i…