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 1121–1130 of 1135 papers

TitleStatusHype
Pre-Learning Environment Representations for Data-Efficient Neural Instruction FollowingCode0
Chasing Ghosts: Instruction Following as Bayesian State TrackingCode0
Language as an Abstraction for Hierarchical Deep Reinforcement LearningCode0
A Survey of Reinforcement Learning Informed by Natural Language—0
Stay on the Path: Instruction Fidelity in Vision-and-Language Navigation—0
Compositional pre-training for neural semantic parsing—0
Learning To Follow Directions in Street ViewCode0
From Language to Goals: Inverse Reinforcement Learning for Vision-Based Instruction Following—0
Learning to Navigate the Web—0
Guiding Policies with Language via Meta-LearningCode0
Show:102550
← PrevPage 113 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