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

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Showing 526–550 of 1135 papers

TitleStatusHype
PediaBench: A Comprehensive Chinese Pediatric Dataset for Benchmarking Large Language ModelsCode0
Toward Zero-Shot Instruction FollowingCode0
Align^2LLaVA: Cascaded Human and Large Language Model Preference Alignment for Multi-modal Instruction CurationCode0
CoEvol: Constructing Better Responses for Instruction Finetuning through Multi-Agent CooperationCode0
NatSGLD: A Dataset with Speech, Gesture, Logic, and Demonstration for Robot Learning in Natural Human-Robot InteractionCode0
FMDLlama: Financial Misinformation Detection based on Large Language ModelsCode0
MuSC: Improving Complex Instruction Following with Multi-granularity Self-Contrastive TrainingCode0
MpoxVLM: A Vision-Language Model for Diagnosing Skin Lesions from Mpox Virus InfectionCode0
CoDe: Blockwise Control for Denoising Diffusion ModelsCode0
Find the Intention of Instruction: Comprehensive Evaluation of Instruction Understanding for Large Language ModelsCode0
CoDa: Constrained Generation based Data Augmentation for Low-Resource NLPCode0
FFT: Towards Harmlessness Evaluation and Analysis for LLMs with Factuality, Fairness, ToxicityCode0
Multi-Level Compositional Reasoning for Interactive Instruction FollowingCode0
Empowering Persian LLMs for Instruction Following: A Novel Dataset and Training ApproachCode0
Monolingual or Multilingual Instruction Tuning: Which Makes a Better AlpacaCode0
FALCON: Feedback-driven Adaptive Long/short-term memory reinforced Coding Optimization systemCode0
ASMA-Tune: Unlocking LLMs' Assembly Code Comprehension via Structural-Semantic Instruction TuningCode0
Mitigating the Bias of Large Language Model EvaluationCode0
MLAN: Language-Based Instruction Tuning Improves Zero-Shot Generalization of Multimodal Large Language ModelsCode0
A safety realignment framework via subspace-oriented model fusion for large language modelsCode0
MIMO: A Medical Vision Language Model with Visual Referring Multimodal Input and Pixel Grounding Multimodal OutputCode0
MM-R5: MultiModal Reasoning-Enhanced ReRanker via Reinforcement Learning for Document RetrievalCode0
Phased Instruction Fine-Tuning for Large Language ModelsCode0
MDCure: A Scalable Pipeline for Multi-Document Instruction-FollowingCode0
Evaluating the Instruction-following Abilities of Language Models using Knowledge TasksCode0
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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