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 121–130 of 1135 papers

TitleStatusHype
UAV-VLN: End-to-End Vision Language guided Navigation for UAVs—0
TF1-EN-3M: Three Million Synthetic Moral Fables for Training Small, Open Language ModelsCode0
CachePrune: Neural-Based Attribution Defense Against Indirect Prompt Injection Attacks—0
Breaking the Modality Barrier: Universal Embedding Learning with Multimodal LLMs—0
ParamΔ for Direct Weight Mixing: Post-Train Large Language Model at Zero Cost—0
ManipDreamer: Boosting Robotic Manipulation World Model with Action Tree and Visual Guidance—0
Case Study: Fine-tuning Small Language Models for Accurate and Private CWE Detection in Python Code—0
Instruction-Tuning Data Synthesis from Scratch via Web ReconstructionCode1
Evaluating Judges as Evaluators: The JETTS Benchmark of LLM-as-Judges as Test-Time Scaling EvaluatorsCode0
DistilQwen2.5: Industrial Practices of Training Distilled Open Lightweight Language Models—0
Show:102550
← PrevPage 13 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