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

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Showing 721–730 of 1135 papers

TitleStatusHype
LeVERB: Humanoid Whole-Body Control with Latent Vision-Language Instruction—0
Compositional pre-training for neural semantic parsing—0
LEWIS (LayEr WIse Sparsity) -- A Training Free Guided Model Merging Approach—0
ThinkBot: Embodied Instruction Following with Thought Chain Reasoning—0
Thinking LLMs: General Instruction Following with Thought Generation—0
LIDAO: Towards Limited Interventions for Debiasing (Large) Language Models—0
LiDAR-LLM: Exploring the Potential of Large Language Models for 3D LiDAR Understanding—0
LIMIT: Less Is More for Instruction Tuning Across Evaluation Paradigms—0
Compositional Instruction Following with Language Models and Reinforcement Learning—0
ThinkLess: A Training-Free Inference-Efficient Method for Reducing Reasoning Redundancy—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