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cs.AI2024
VLASCD: A Visual Language Action Model for Simultaneous Chatting and Decision Making
Zuojin Tang, Bin Hu, Chenyang Zhao +3
Recent large pretrained models such as LLMs (e.g., GPT series) and VLAs (e.g., OpenVLA) have achieved notable progress on multimodal tasks, yet they are built upon a multi-input si…
cs.CL2024
Benchmarking Complex Instruction-Following with Multiple Constraints Composition
Bosi Wen, Pei Ke, Xiaotao Gu +11
Instruction following is one of the fundamental capabilities of large language models (LLMs). As the ability of LLMs is constantly improving, they have been increasingly applied to…
cs.AI2024★ 1 cited
Bug In the Code Stack: Can LLMs Find Bugs in Large Python Code Stacks
Hokyung Lee, Sumanyu Sharma, Bing Hu
Recent research in Needle-in-a-Haystack (NIAH) benchmarks has explored the capabilities of Large Language Models (LLMs) in retrieving contextual information from large text documen…