773 citations · 781 across the 8 of their papers we have counts for
8 papers
CodecCap: High-Fidelity Codec-Inspired Residual Modeling for Dense Video Captioning
Zihan Lin, Songhe Deng, Shuwei He +6
Existing video captioning methods struggle to balance visual fidelity and redundancy: holistic captions are compact but lose fine-grained evidence, whereas segment-wise captions im…
Eureka-Audio: Triggering Audio Intelligence in Compact Language Models
Dan Zhang, Yishu Lei, Jing Hu +10
We present Eureka-Audio, a compact yet high-performance audio language model that achieves competitive performance against models that are 4 to 18 times larger across a broad range…
ERNIE 5.0 Technical Report
Haifeng Wang, Hua Wu, Tian Wu +432
In this report, we introduce ERNIE 5.0, a natively autoregressive foundation model desinged for unified multimodal understanding and generation across text, image, video, and audio…
CORD: Bridging the Audio-Text Reasoning Gap via Weighted On-policy Cross-modal Distillation
Jing Hu, Danxiang Zhu, Xianlong Luo +9
Large Audio Language Models (LALMs) have garnered significant research interest. Despite being built upon text-based large language models (LLMs), LALMs frequently exhibit a degrad…
MoE Adapter for Large Audio Language Models: Sparsity, Disentanglement, and Gradient-Conflict-Free
Yishu Lei, Shuwei He, Jing Hu +9
Extending the input modality of Large Language Models~(LLMs) to the audio domain is essential for achieving comprehensive multimodal perception. However, it is well-known that acou…
MatryoshkaThinking: Recursive Test-Time Scaling Enables Efficient Reasoning
Hongwei Chen, Yishu Lei, Dan Zhang +10
Test-time scaling has emerged as a promising paradigm in language modeling, wherein additional computational resources are allocated during inference to enhance model performance.…
WellDunn: On the Robustness and Explainability of Language Models and Large Language Models in Identifying Wellness Dimensions
Seyedali Mohammadi, Edward Raff, Jinendra Malekar +3
Language Models (LMs) are being proposed for mental health applications where the heightened risk of adverse outcomes means predictive performance may not be a sufficient litmus te…
ERNIE: Enhanced Representation through Knowledge Integration
Yu Sun, Shuohuan Wang, Yukun Li +7
We present a novel language representation model enhanced by knowledge called ERNIE (Enhanced Representation through kNowledge IntEgration). Inspired by the masking strategy of BER…