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
FFT: Towards Harmlessness Evaluation and Analysis for LLMs with Factuality, Fairness, ToxicityCode0
Adversarial Moment-Matching Distillation of Large Language ModelsCode0
Instruct-SkillMix: A Powerful Pipeline for LLM Instruction TuningCode0
Rate, Explain and Cite (REC): Enhanced Explanation and Attribution in Automatic Evaluation by Large Language ModelsCode0
InstUPR : Instruction-based Unsupervised Passage Reranking with Large Language ModelsCode0
Zero-shot LLM-guided Counterfactual Generation: A Case Study on NLP Model EvaluationCode0
Do LLMs estimate uncertainty well in instruction-following?Code0
Look Wide and Interpret Twice: Improving Performance on Interactive Instruction-following TasksCode0
Internal Causal Mechanisms Robustly Predict Language Model Out-of-Distribution BehaviorsCode0
WildIFEval: Instruction Following in the WildCode0
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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