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 1101–1125 of 1135 papers

TitleStatusHype
Generalization in Instruction Following Systems—0
PanGEA: The Panoramic Graph Environment Annotation Toolkit—0
Are We There Yet? Learning to Localize in Embodied Instruction Following—0
Spatial Language Understanding for Object Search in Partially Observed City-scale EnvironmentsCode0
From “Before” to “After”: Generating Natural Language Instructions from Image Pairs in a Simple Visual Domain—0
Modular Networks for Compositional Instruction Following—0
Learning to Recombine and Resample Data for Compositional GeneralizationCode0
Inverse Reinforcement Learning with Natural Language Goals—0
Evolving Graphical Planner: Contextual Global Planning for Vision-and-Language Navigation—0
Language-Conditioned Goal Generation: a New Approach to Language Grounding in RL—0
Language-Conditioned Goal Generation: a New Approach to Language Grounding for RL—0
Human Instruction-Following with Deep Reinforcement Learning via Transfer-Learning from Text—0
Language Conditioned Imitation Learning over Unstructured Data—0
Following Instructions by Imagining and Reaching Visual Goals—0
Automated curriculum generation for Policy Gradients from DemonstrationsCode0
Language-guided Semantic Mapping and Mobile Manipulation in Partially Observable Environments—0
HIGhER : Improving instruction following with Hindsight Generation for Experience Replay—0
Robust Instruction-Following in a Situated Agent via Transfer-Learning from Text—0
Self-Educated Language Agent with Hindsight Experience Replay for Instruction Following—0
Guided Adaptive Credit Assignment for Sample Efficient Policy Optimization—0
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
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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