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 911–920 of 1135 papers

TitleStatusHype
Towards LLM-guided Causal Explainability for Black-box Text Classifiers—0
Frustrated with Code Quality Issues? LLMs can Help!—0
AceGPT, Localizing Large Language Models in ArabicCode1
LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation DatasetCode7
LongLoRA: Efficient Fine-tuning of Long-Context Large Language ModelsCode6
Natural Language Embedded Programs for Hybrid Language Symbolic ReasoningCode1
Instruction-Following Speech Recognition—0
Monolingual or Multilingual Instruction Tuning: Which Makes a Better AlpacaCode0
Sorted LLaMA: Unlocking the Potential of Intermediate Layers of Large Language Models for Dynamic Inference—0
TextBind: Multi-turn Interleaved Multimodal Instruction-following in the WildCode1
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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