1 citations · 1 across the 6 of their papers we have counts for
7 papers
LoopAhead: Speculating Ahead for Faster Decoding in Looped Language Models
Zixuan Liu, Nan Xue, Rui Bao +4
Looped Transformers improve parameter efficiency by repeatedly applying the same Transformer layers. However, generating each token still involves sequential computation and repeat…
Unified Hallucination Fuzzing for Multimodal Large Language Models
Pengfei Zhou, Jiajun Song, Zhiwei Tang +12
Hallucination remains a persistent challenge for Multimodal Large Language Models (MLLMs), severely limiting their reliability in high-stakes applications. Existing evaluations, pr…
Programming with Data: Test-Driven Data Engineering for Self-Improving LLMs from Raw Corpora
Chenkai Pan, Xinglong Xu, Yuhang Xu +6
Reliably transferring specialized human knowledge from text into large language models remains a fundamental challenge in artificial intelligence. Fine-tuning on domain corpora has…
SmartThinker: Progressive Chain-of-Thought Length Calibration for Efficient Large Language Model Reasoning
Chenzhi Hu, Qinzhe Hu, Yuhang Xu +6
Large reasoning models (LRMs) like OpenAI o1 and DeepSeek-R1 achieve high accuracy on complex tasks by adopting long chain-of-thought (CoT) reasoning paths. However, the inherent v…
The Trinity of Consistency as a Defining Principle for General World Models
Jingxuan Wei, Siyuan Li, Yuhang Xu +21
The construction of World Models capable of learning, simulating, and reasoning about objective physical laws constitutes a foundational challenge in the pursuit of Artificial Gene…
Thinking with Drafting: Optical Decompression via Logical Reconstruction
Jingxuan Wei, Honghao He, Caijun Jia +9
Existing multimodal large language models have achieved high-fidelity visual perception and exploratory visual generation. However, a precision paradox persists in complex reasonin…
Seed1.5-VL Technical Report
Dong Guo, Faming Wu, Feida Zhu +194
We present Seed1.5-VL, a vision-language foundation model designed to advance general-purpose multimodal understanding and reasoning. Seed1.5-VL is composed with a 532M-parameter v…