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 401–410 of 1135 papers

TitleStatusHype
Language Imbalance Driven Rewarding for Multilingual Self-improvingCode1
Reward-Augmented Data Enhances Direct Preference Alignment of LLMsCode1
CoPESD: A Multi-Level Surgical Motion Dataset for Training Large Vision-Language Models to Co-Pilot Endoscopic Submucosal DissectionCode1
Evolutionary Contrastive Distillation for Language Model Alignment—0
Instructional Segment Embedding: Improving LLM Safety with Instruction Hierarchy—0
Large Language Model Compression with Neural Architecture Search—0
HERM: Benchmarking and Enhancing Multimodal LLMs for Human-Centric Understanding—0
LLM Self-Correction with DeCRIM: Decompose, Critique, and Refine for Enhanced Following of Instructions with Multiple Constraints—0
ReIFE: Re-evaluating Instruction-Following EvaluationCode0
Self-Boosting Large Language Models with Synthetic Preference Data—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