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 291–300 of 1135 papers

TitleStatusHype
Align Anything: Training All-Modality Models to Follow Instructions with Language FeedbackCode7
HREF: Human Response-Guided Evaluation of Instruction Following in Language ModelsCode0
Length Controlled Generation for Black-box LLMs—0
Qwen2.5 Technical ReportCode13
Systematic Evaluation of Long-Context LLMs on Financial Concepts—0
A Systematic Examination of Preference Learning through the Lens of Instruction-Following—0
MetaMorph: Multimodal Understanding and Generation via Instruction Tuning—0
Pipeline Analysis for Developing Instruct LLMs in Low-Resource Languages: A Case Study on Basque—0
Question: How do Large Language Models perform on the Question Answering tasks? Answer:—0
LLaVA Steering: Visual Instruction Tuning with 500x Fewer Parameters through Modality Linear Representation-SteeringCode0
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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