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 161–170 of 1135 papers

TitleStatusHype
EarthGPT: A Universal Multi-modal Large Language Model for Multi-sensor Image Comprehension in Remote Sensing DomainCode2
LLaVA-MORE: A Comparative Study of LLMs and Visual Backbones for Enhanced Visual Instruction TuningCode2
AIR-Bench: Benchmarking Large Audio-Language Models via Generative ComprehensionCode2
EcomGPT: Instruction-tuning Large Language Models with Chain-of-Task Tasks for E-commerceCode2
Diffusion-ES: Gradient-free Planning with Diffusion for Autonomous Driving and Zero-Shot Instruction FollowingCode2
DistiLLM-2: A Contrastive Approach Boosts the Distillation of LLMsCode2
Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free LunchCode2
Archon: An Architecture Search Framework for Inference-Time TechniquesCode2
Dual-Space Knowledge Distillation for Large Language ModelsCode2
LLark: A Multimodal Instruction-Following Language Model for MusicCode2
Show:102550
← PrevPage 17 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