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 1001–1025 of 1135 papers

TitleStatusHype
LLaVA Steering: Visual Instruction Tuning with 500x Fewer Parameters through Modality Linear Representation-SteeringCode0
Bayesian Calibration of Win Rate Estimation with LLM EvaluatorsCode0
Teaching Llama a New Language Through Cross-Lingual Knowledge TransferCode0
DoG-Instruct: Towards Premium Instruction-Tuning Data via Text-Grounded Instruction WrappingCode0
LLM as Dataset Analyst: Subpopulation Structure Discovery with Large Language ModelCode0
HalLoc: Token-level Localization of Hallucinations for Vision Language ModelsCode0
FALCON: Feedback-driven Adaptive Long/short-term memory reinforced Coding Optimization systemCode0
Empowering Persian LLMs for Instruction Following: A Novel Dataset and Training ApproachCode0
Towards Robust Instruction Tuning on Multimodal Large Language ModelsCode0
MuSC: Improving Complex Instruction Following with Multi-granularity Self-Contrastive TrainingCode0
InstructAny2Pix: Flexible Visual Editing via Multimodal Instruction FollowingCode0
A safety realignment framework via subspace-oriented model fusion for large language modelsCode0
Quantifying Self-diagnostic Atomic Knowledge in Chinese Medical Foundation Model: A Computational AnalysisCode0
NatSGLD: A Dataset with Speech, Gesture, Logic, and Demonstration for Robot Learning in Natural Human-Robot InteractionCode0
Instruction Clarification Requests in Multimodal Collaborative Dialogue Games: Tasks, and an Analysis of the CoDraw DatasetCode0
Analysis of Language Change in Collaborative Instruction FollowingCode0
T-REG: Preference Optimization with Token-Level Reward RegularizationCode0
Spatial Language Understanding for Object Search in Partially Observed City-scale EnvironmentsCode0
GoalNet: Inferring Conjunctive Goal Predicates from Human Plan Demonstrations for Robot Instruction FollowingCode0
How You Prompt Matters! Even Task-Oriented Constraints in Instructions Affect LLM-Generated Text DetectionCode0
Localized Symbolic Knowledge Distillation for Visual Commonsense ModelsCode0
Hierarchical Modular Framework for Long Horizon Instruction FollowingCode0
Instruction Following with Goal-Conditioned Reinforcement Learning in Virtual EnvironmentsCode0
Aligners: Decoupling LLMs and AlignmentCode0
AdaPPA: Adaptive Position Pre-Fill Jailbreak Attack Approach Targeting LLMsCode0
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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