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 81–90 of 1135 papers

TitleStatusHype
ThinkLess: A Training-Free Inference-Efficient Method for Reducing Reasoning Redundancy—0
Diffusion vs. Autoregressive Language Models: A Text Embedding Perspective—0
Hunyuan-TurboS: Advancing Large Language Models through Mamba-Transformer Synergy and Adaptive Chain-of-Thought—0
FlowKV: Enhancing Multi-Turn Conversational Coherence in LLMs via Isolated Key-Value Cache Management—0
Joint Flashback Adaptation for Forgetting-Resistant Instruction Tuning—0
Scaling Reasoning, Losing Control: Evaluating Instruction Following in Large Reasoning ModelsCode1
Domain Adaptation of VLM for Soccer Video Understanding—0
Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training—0
DecIF: Improving Instruction-Following through Meta-Decomposition—0
Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels—0
Show:102550
← PrevPage 9 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