180 citations · 243 across the 28 of their papers we have counts for
13 papers · 1 filter
GLM-TTS Technical Report
Jiayan Cui, Zhihan Yang, Naihan Li +10
This work proposes GLM-TTS, a production-level TTS system designed for efficiency, controllability, and high-fidelity speech generation. GLM-TTS follows a two-stage architecture, c…
SCAIL: Towards Studio-Grade Character Animation via In-Context Learning of 3D-Consistent Pose Representations
Wenhao Yan, Sheng Ye, Zhuoyi Yang +6
Achieving controllable character animation that meets studio-grade standards remains challenging despite recent progress. Existing approaches can transfer motion from a driving vid…
Delving into Latent Spectral Biasing of Video VAEs for Superior Diffusability
Shizhan Liu, Xinran Deng, Zhuoyi Yang +3
Latent diffusion models pair VAEs with diffusion backbones, and the structure of VAE latents strongly influences the difficulty of diffusion training. However, existing video VAEs…
WebVIA: A Web-based Vision-Language Agentic Framework for Interactive and Verifiable UI-to-Code Generation
Mingde Xu, Zhen Yang, Wenyi Hong +6
User interface (UI) development requires translating design mockups into functional code, a process that remains repetitive and labor-intensive. While recent Vision-Language Models…
UI2Code^N: UI-to-Code Generation as Interactive Visual Optimization
Zhen Yang, Wenyi Hong, Mingde Xu +5
UI-to-code aims to translate UI screenshots into executable front-end code. Despite progress with vision-language models (VLMs), most existing methods formulate UI-to-code as a sin…
InvestAlign: Overcoming Data Scarcity in Aligning Large Language Models with Investor Decision-Making Processes under Herd Behavior
Huisheng Wang, Zhuoshi Pan, Hangjing Zhang +3
Aligning Large Language Models (LLMs) with investor decision-making processes under herd behavior is a critical challenge in behavioral finance, which grapples with a fundamental l…
GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning
V Team, Wenyi Hong, Wenmeng Yu +90
We present GLM-4.1V-Thinking, GLM-4.5V, and GLM-4.6V, a family of vision-language models (VLMs) designed to advance general-purpose multimodal understanding and reasoning. In this…
StepMathAgent: A Step-Wise Agent for Evaluating Mathematical Processes through Tree-of-Error
Shu-Xun Yang, Cunxiang Wang, Yidong Wang +3
Evaluating mathematical capabilities is critical for assessing the overall performance of large language models (LLMs). However, existing evaluation methods often focus solely on f…
VPO: Aligning Text-to-Video Generation Models with Prompt Optimization
Jiale Cheng, Ruiliang Lyu, Xiaotao Gu +9
Video generation models have achieved remarkable progress in text-to-video tasks. These models are typically trained on text-video pairs with highly detailed and carefully crafted…
Concat-ID: Towards Universal Identity-Preserving Video Synthesis
Yong Zhong, Zhuoyi Yang, Jiayan Teng +2
We present Concat-ID, a unified framework for identity-preserving video generation. Concat-ID employs variational autoencoders to extract image features, which are then concatenate…
LongSafety: Evaluating Long-Context Safety of Large Language Models
Yida Lu, Jiale Cheng, Zhexin Zhang +7
As Large Language Models (LLMs) continue to advance in understanding and generating long sequences, new safety concerns have been introduced through the long context. However, the…
HPSS: Heuristic Prompting Strategy Search for LLM Evaluators
Bosi Wen, Pei Ke, Yufei Sun +6
Since the adoption of large language models (LLMs) for text evaluation has become increasingly prevalent in the field of natural language processing (NLP), a series of existing wor…
MotionBench: Benchmarking and Improving Fine-grained Video Motion Understanding for Vision Language Models
Wenyi Hong, Yean Cheng, Zhuoyi Yang +6
In recent years, vision language models (VLMs) have made significant advancements in video understanding. However, a crucial capability - fine-grained motion comprehension - remain…