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 831–840 of 1135 papers

TitleStatusHype
OmniJARVIS: Unified Vision-Language-Action Tokenization Enables Open-World Instruction Following Agents—0
Role-Play Zero-Shot Prompting with Large Language Models for Open-Domain Human-Machine Conversation—0
A Text is Worth Several Tokens: Text Embedding from LLMs Secretly Aligns Well with The Key Tokens—0
Following Length Constraints in Instructions—0
Evaluation of Instruction-Following Ability for Large Language Models on Story-Ending Generation—0
Teach Better or Show Smarter? On Instructions and Exemplars in Automatic Prompt Optimization—0
AdaGrad under Anisotropic Smoothness—0
DEM: Distribution Edited Model for Training with Mixed Data Distributions—0
IWISDM: Assessing instruction following in multimodal models at scaleCode0
VLM Agents Generate Their Own Memories: Distilling Experience into Embodied Programs of Thought—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