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 531–540 of 1135 papers

TitleStatusHype
Benchmarking Complex Instruction-Following with Multiple Constraints CompositionCode2
FunAudioLLM: Voice Understanding and Generation Foundation Models for Natural Interaction Between Humans and LLMsCode11
Diverse and Fine-Grained Instruction-Following Ability Exploration with Synthetic Data—0
D-Rax: Domain-specific Radiologic assistant leveraging multi-modal data and eXpert model predictions—0
Pelican: Correcting Hallucination in Vision-LLMs via Claim Decomposition and Program of Thought Verification—0
Improving Multilingual Instruction Finetuning via Linguistically Natural and Diverse Datasets—0
MIA-Bench: Towards Better Instruction Following Evaluation of Multimodal LLMsCode1
Iterative Data Generation with Large Language Models for Aspect-based Sentiment Analysis—0
MM-Instruct: Generated Visual Instructions for Large Multimodal Model AlignmentCode1
ScaleBiO: Scalable Bilevel Optimization for LLM Data Reweighting—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