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 481–490 of 1135 papers

TitleStatusHype
MASTER: Enhancing Large Language Model via Multi-Agent Simulated Teaching—0
TIIF-Bench: How Does Your T2I Model Follow Your Instructions?—0
MoDA: Modulation Adapter for Fine-Grained Visual Grounding in Instructional MLLMs—0
PersianMedQA: Language-Centric Evaluation of LLMs in the Persian Medical Domain—0
Differential Information: An Information-Theoretic Perspective on Preference Optimization—0
ChartMind: A Comprehensive Benchmark for Complex Real-world Multimodal Chart Question Answering—0
ARC: Argument Representation and Coverage Analysis for Zero-Shot Long Document Summarization with Instruction Following LLMs—0
Adaptive Detoxification: Safeguarding General Capabilities of LLMs through Toxicity-Aware Knowledge Editing—0
LaMDAgent: An Autonomous Framework for Post-Training Pipeline Optimization via LLM Agents—0
PartInstruct: Part-level Instruction Following for Fine-grained Robot Manipulation—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