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 1021–1030 of 1135 papers

TitleStatusHype
Benchmarking and Improving Generator-Validator Consistency of Language Models—0
PACIT: Unlocking the Power of Examples for Better In-Context Instruction TuningCode0
SLM: Bridge the thin gap between speech and text foundation models—0
Self-Specialization: Uncovering Latent Expertise within Large Language Models—0
Towards LLM-guided Causal Explainability for Black-box Text Classifiers—0
Frustrated with Code Quality Issues? LLMs can Help!—0
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
Quantifying and Attributing the Hallucination of Large Language Models via Association Analysis—0
Show:102550
← PrevPage 103 of 114Next →

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