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 51–60 of 1135 papers

TitleStatusHype
Don't Reinvent the Wheel: Efficient Instruction-Following Text Embedding based on Guided Space TransformationCode1
When Large Multimodal Models Confront Evolving Knowledge:Challenges and PathwaysCode2
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
Differential Information: An Information-Theoretic Perspective on Preference Optimization—0
LaMDAgent: An Autonomous Framework for Post-Training Pipeline Optimization via LLM Agents—0
Adaptive Detoxification: Safeguarding General Capabilities of LLMs through Toxicity-Aware Knowledge Editing—0
Let Them Talk: Audio-Driven Multi-Person Conversational Video GenerationCode7
A Course Correction in Steerability Evaluation: Revealing Miscalibration and Side Effects in LLMsCode0
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