2 citations · 9 across the 8 of their papers we have counts for
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cs.AI2024★ 2 cited
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…
cs.CL2024★ 2 cited
Balancing Enhancement, Harmlessness, and General Capabilities: Enhancing Conversational LLMs with Direct RLHF
Chen Zheng, Ke Sun, Hang Wu +2
In recent advancements in Conversational Large Language Models (LLMs), a concerning trend has emerged, showing that many new base LLMs experience a knowledge reduction in their fou…
cs.CL2024
ICE-GRT: Instruction Context Enhancement by Generative Reinforcement based Transformers
Chen Zheng, Ke Sun, Da Tang +4
The emergence of Large Language Models (LLMs) such as ChatGPT and LLaMA encounter limitations in domain-specific tasks, with these models often lacking depth and accuracy in specia…