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 931–940 of 1135 papers

TitleStatusHype
Sparkles: Unlocking Chats Across Multiple Images for Multimodal Instruction-Following ModelsCode1
LLaSM: Large Language and Speech ModelCode2
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
Code Llama: Open Foundation Models for CodeCode6
Improving Translation Faithfulness of Large Language Models via Augmenting InstructionsCode1
Instruction Position Matters in Sequence Generation with Large Language ModelsCode1
From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction TuningCode2
InstructionGPT-4: A 200-Instruction Paradigm for Fine-Tuning MiniGPT-4Code1
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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