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 521–530 of 1135 papers

TitleStatusHype
CommonIT: Commonality-Aware Instruction Tuning for Large Language Models via Data PartitionsCode0
Multi-Level Compositional Reasoning for Interactive Instruction FollowingCode0
MpoxVLM: A Vision-Language Model for Diagnosing Skin Lesions from Mpox Virus InfectionCode0
Exploring the Trade-Offs: Quantization Methods, Task Difficulty, and Model Size in Large Language Models From Edge to GiantCode0
Toward Zero-Shot Instruction FollowingCode0
Align^2LLaVA: Cascaded Human and Large Language Model Preference Alignment for Multi-modal Instruction CurationCode0
CoEvol: Constructing Better Responses for Instruction Finetuning through Multi-Agent CooperationCode0
Monolingual or Multilingual Instruction Tuning: Which Makes a Better AlpacaCode0
FMDLlama: Financial Misinformation Detection based on Large Language ModelsCode0
MM-R5: MultiModal Reasoning-Enhanced ReRanker via Reinforcement Learning for Document RetrievalCode0
Show:102550
← PrevPage 53 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