3 citations · 5 across the 4 of their papers we have counts for
4 papers
FullStack Bench: Evaluating LLMs as Full Stack Coders
Bytedance-Seed-Foundation-Code-Team, :, Yao Cheng +53
As the capabilities of code large language models (LLMs) continue to expand, their applications across diverse code intelligence domains are rapidly increasing. However, most exist…
BabelBench: An Omni Benchmark for Code-Driven Analysis of Multimodal and Multistructured Data
Xuwu Wang, Qiwen Cui, Yunzhe Tao +16
Large language models (LLMs) have become increasingly pivotal across various domains, especially in handling complex data types. This includes structured data processing, as exempl…
LEMON: Lossless model expansion
Yite Wang, Jiahao Su, Hanlin Lu +6
Scaling of deep neural networks, especially Transformers, is pivotal for their surging performance and has further led to the emergence of sophisticated reasoning capabilities in f…
Let Models Speak Ciphers: Multiagent Debate through Embeddings
Chau Pham, Boyi Liu, Yingxiang Yang +6
Discussion and debate among Large Language Models (LLMs) have gained considerable attention due to their potential to enhance the reasoning ability of LLMs. Although natural langua…