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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 981–990 of 1135 papers

TitleStatusHype
MUFFIN: Curating Multi-Faceted Instructions for Improving Instruction-Following—0
InstructBooth: Instruction-following Personalized Text-to-Image Generation—0
MedXChat: A Unified Multimodal Large Language Model Framework towards CXRs Understanding and Generation—0
FFT: Towards Harmlessness Evaluation and Analysis for LLMs with Factuality, Fairness, ToxicityCode0
Towards Vision Enhancing LLMs: Empowering Multimodal Knowledge Storage and Sharing in LLMs—0
Releasing the CRaQAn (Coreference Resolution in Question-Answering): An open-source dataset and dataset creation methodology using instruction-following models—0
GPT4Video: A Unified Multimodal Large Language Model for lnstruction-Followed Understanding and Safety-Aware Generation—0
LIMIT: Less Is More for Instruction Tuning Across Evaluation Paradigms—0
Data Diversity Matters for Robust Instruction Tuning—0
RecExplainer: Aligning Large Language Models for Explaining Recommendation Models—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