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 1051–1060 of 1135 papers

TitleStatusHype
Instruction Mining: Instruction Data Selection for Tuning Large Language Models—0
Becoming self-instruct: introducing early stopping criteria for minimal instruct tuning—0
Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control—0
KITE: Keypoint-Conditioned Policies for Semantic Manipulation—0
CorNav: Autonomous Agent with Self-Corrected Planning for Zero-Shot Vision-and-Language Navigation—0
"Are you telling me to put glasses on the dog?'' Content-Grounded Annotation of Instruction Clarification Requests in the CoDraw Dataset—0
Controllable Text-to-Image Generation with GPT-4—0
A Reminder of its Brittleness: Language Reward Shaping May Hinder Learning for Instruction Following AgentsCode0
SAIL: Search-Augmented Instruction Learning—0
A Monte Carlo Language Model Pipeline for Zero-Shot Sociopolitical Event Extraction—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