5 papers · 1 filter
OS Agents: A Survey on MLLM-based Agents for General Computing Devices Use
Xueyu Hu, Tao Xiong, Biao Yi +26
The dream to create AI assistants as capable and versatile as the fictional J.A.R.V.I.S from Iron Man has long captivated imaginations. With the evolution of (multi-modal) large la…
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…
LoraRetriever: Input-Aware LoRA Retrieval and Composition for Mixed Tasks in the Wild
Ziyu Zhao, Leilei Gan, Guoyin Wang +4
Low-Rank Adaptation (LoRA) provides an effective yet efficient solution for fine-tuning large language models (LLM). The modular and plug-and-play nature of LoRA enables the integr…
Empowering Large Language Model Agents through Action Learning
Haiteng Zhao, Chang Ma, Guoyin Wang +5
Large Language Model (LLM) Agents have recently garnered increasing interest yet they are limited in their ability to learn from trial and error, a key element of intelligent behav…