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 251–275 of 1135 papers

TitleStatusHype
Hybrid Alignment Training for Large Language ModelsCode1
AllenAct: A Framework for Embodied AI ResearchCode1
LLM-CXR: Instruction-Finetuned LLM for CXR Image Understanding and GenerationCode1
Beyond Task Performance: Evaluating and Reducing the Flaws of Large Multimodal Models with In-Context LearningCode1
CrowdSelect: Synthetic Instruction Data Selection with Multi-LLM WisdomCode1
Bactrian-X: Multilingual Replicable Instruction-Following Models with Low-Rank AdaptationCode1
LoGU: Long-form Generation with Uncertainty ExpressionsCode1
Cross-model Control: Improving Multiple Large Language Models in One-time TrainingCode1
Back to the Future: Towards Explainable Temporal Reasoning with Large Language ModelsCode1
Zero-Shot Compositional Policy Learning via Language GroundingCode1
Aya Dataset: An Open-Access Collection for Multilingual Instruction TuningCode1
Creative Agents: Empowering Agents with Imagination for Creative TasksCode1
Counterfactual Cycle-Consistent Learning for Instruction Following and Generation in Vision-Language NavigationCode1
IDA-Bench: Evaluating LLMs on Interactive Guided Data AnalysisCode1
LLaMo: Large Language Model-based Molecular Graph AssistantCode1
LLaSA: A Multimodal LLM for Human Activity Analysis Through Wearable and Smartphone SensorsCode1
CoPESD: A Multi-Level Surgical Motion Dataset for Training Large Vision-Language Models to Co-Pilot Endoscopic Submucosal DissectionCode1
CoachLM: Automatic Instruction Revisions Improve the Data Quality in LLM Instruction TuningCode1
Guiding Multi-Step Rearrangement Tasks with Natural Language InstructionsCode1
Contrastive Vision-Language Alignment Makes Efficient Instruction LearnerCode1
HalluciDoctor: Mitigating Hallucinatory Toxicity in Visual Instruction DataCode1
Aligning Instruction Tasks Unlocks Large Language Models as Zero-Shot Relation ExtractorsCode1
AutoDetect: Towards a Unified Framework for Automated Weakness Detection in Large Language ModelsCode1
Context-Aware Planning and Environment-Aware Memory for Instruction Following Embodied AgentsCode1
Constraint Back-translation Improves Complex Instruction Following of Large Language ModelsCode1
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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