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 1021–1030 of 1135 papers

TitleStatusHype
Tests as Prompt: A Test-Driven-Development Benchmark for LLM Code Generation—0
Instruction Tuning on Public Government and Cultural Data for Low-Resource Language: a Case Study in Kazakh—0
CycleAlign: Iterative Distillation from Black-box LLM to White-box Models for Better Human Alignment—0
Text as Image: Learning Transferable Adapter for Multi-Label Classification—0
Only-IF:Revealing the Decisive Effect of Instruction Diversity on Generalization—0
Integrating Arithmetic Learning Improves Mathematical Reasoning in Smaller Models—0
Failures to Find Transferable Image Jailbreaks Between Vision-Language Models—0
Internalized Self-Correction for Large Language Models—0
InternLM-XComposer2.5-Reward: A Simple Yet Effective Multi-Modal Reward Model—0
Refine Large Language Model Fine-tuning via Instruction Vector—0
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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