12 citations · 14 across the 12 of their papers we have counts for
7 papers · 1 filter
Qwen-Image-Layered: Towards Inherent Editability via Layer Decomposition
Shengming Yin, Zekai Zhang, Zecheng Tang +11
Recent visual generative models often struggle with consistency during image editing due to the entangled nature of raster images, where all visual content is fused into a single c…
Omni-Captioner: Data Pipeline, Models, and Benchmark for Omni Detailed Perception
Ziyang Ma, Ruiyang Xu, Zhenghao Xing +9
Fine-grained perception of multimodal information is critical for advancing human-AI interaction. With recent progress in audio-visual technologies, Omni Language Models (OLMs), ca…
ContextASR-Bench: A Massive Contextual Speech Recognition Benchmark
He Wang, Linhan Ma, Dake Guo +4
Automatic Speech Recognition (ASR) has been extensively investigated, yet prior benchmarks have largely focused on assessing the acoustic robustness of ASR models, leaving evaluati…
WavReward: Spoken Dialogue Models With Generalist Reward Evaluators
Shengpeng Ji, Tianle Liang, Yangzhuo Li +11
End-to-end spoken dialogue models such as GPT-4o-audio have recently garnered significant attention in the speech domain. However, the evaluation of spoken dialogue models' convers…
Qwen2.5-Omni Technical Report
Jin Xu, Zhifang Guo, Jinzheng He +11
In this report, we present Qwen2.5-Omni, an end-to-end multimodal model designed to perceive diverse modalities, including text, images, audio, and video, while simultaneously gene…
InSerter: Speech Instruction Following with Unsupervised Interleaved Pre-training
Dingdong Wang, Jin Xu, Ruihang Chu +6
Recent advancements in speech large language models (SpeechLLMs) have attracted considerable attention. Nonetheless, current methods exhibit suboptimal performance in adhering to s…
Efficient Long Context Fine-tuning with Chunk Flow
Xiulong Yuan, Hongtao Xu, Wenting Shen +10
Long context fine-tuning of large language models(LLMs) involves training on datasets that are predominantly composed of short sequences and a small proportion of longer sequences.…