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 1031–1040 of 1135 papers

TitleStatusHype
DoG-Instruct: Towards Premium Instruction-Tuning Data via Text-Grounded Instruction WrappingCode0
Efficient Finetuning Large Language Models For Vietnamese Chatbot—0
Improving Open Information Extraction with Large Language Models: A Study on Demonstration Uncertainty—0
Self-driven Grounding: Large Language Model Agents with Automatical Language-aligned Skill Learning—0
FactLLaMA: Optimizing Instruction-Following Language Models with External Knowledge for Automated Fact-Checking—0
Language-Conditioned Change-point Detection to Identify Sub-Tasks in Robotics DomainsCode0
Evaluating the Robustness to Instructions of Large Language Models—0
Empowering Cross-lingual Abilities of Instruction-tuned Large Language Models by Translation-following demonstrationsCode0
MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records—0
UniDoc: A Universal Large Multimodal Model for Simultaneous Text Detection, Recognition, Spotting and Understanding—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