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 1051–1075 of 1135 papers

TitleStatusHype
UGIF: UI Grounded Instruction Following—0
Learning to Follow Instructions in Text-Based GamesCode0
Prompter: Utilizing Large Language Model Prompting for a Data Efficient Embodied Instruction Following—0
Instruction-Following Agents with Multimodal TransformerCode1
DANLI: Deliberative Agent for Following Natural Language InstructionsCode1
Don't Copy the Teacher: Data and Model Challenges in Embodied DialogueCode0
Efficiently Enhancing Zero-Shot Performance of Instruction Following Model via Retrieval of Soft PromptCode1
A New Path: Scaling Vision-and-Language Navigation with Synthetic Instructions and Imitation Learning—0
Iterative Vision-and-Language Navigation—0
LM-Nav: Robotic Navigation with Large Pre-Trained Models of Language, Vision, and ActionCode2
Language Models are General-Purpose Interfaces—0
GoalNet: Inferring Conjunctive Goal Predicates from Human Plan Demonstrations for Robot Instruction FollowingCode0
Engineering flexible machine learning systems by traversing functionally-invariant pathsCode1
Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP TasksCode3
Inferring Rewards from Language in ContextCode1
Counterfactual Cycle-Consistent Learning for Instruction Following and Generation in Vision-Language NavigationCode1
Summarizing a virtual robot's past actions in natural language—0
Combining Modular Skills in Multitask LearningCode1
DialFRED: Dialogue-Enabled Agents for Embodied Instruction FollowingCode1
Compositionality as Lexical SymmetryCode0
Less is More: Generating Grounded Navigation Instructions from Landmarks—0
Explicit Object Relation Alignment for Vision and Language Navigation—0
Skill Induction and Planning with Latent Language—0
Guiding Multi-Step Rearrangement Tasks with Natural Language InstructionsCode1
Compositional Data and Task Augmentation for Instruction Following—0
Show:102550
← PrevPage 43 of 46Next →

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