SOTAVerified

Instruction Following

Instruction following is the basic task of the model. This task is dedicated to evaluating the ability of the large model to follow human instructions. It is hoped that the model can generate controllable and safe answers.

Papers

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Showing 51–60 of 1135 papers

TitleStatusHype
LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One DayCode4
Otter: A Multi-Modal Model with In-Context Instruction TuningCode4
Instruction Tuning with GPT-4Code4
Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt InjectionCode4
IFEval-Audio: Benchmarking Instruction-Following Capability in Audio-based Large Language ModelsCode3
LaViDa: A Large Diffusion Language Model for Multimodal UnderstandingCode3
LLaMA-Omni2: LLM-based Real-time Spoken Chatbot with Autoregressive Streaming Speech SynthesisCode3
VARGPT-v1.1: Improve Visual Autoregressive Large Unified Model via Iterative Instruction Tuning and Reinforcement LearningCode3
The Breeze 2 Herd of Models: Traditional Chinese LLMs Based on Llama with Vision-Aware and Function-Calling CapabilitiesCode3
VARGPT: Unified Understanding and Generation in a Visual Autoregressive Multimodal Large Language ModelCode3
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AutoIF (Llama3 70B)Inst-level loose-accuracy90.4—Unverified
2AutoIF (Qwen2 72B)Inst-level loose-accuracy88—Unverified
3GPT-4Inst-level loose-accuracy85.37—Unverified
4PaLM 2 SInst-level loose-accuracy59.11—Unverified