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 741–750 of 1135 papers

TitleStatusHype
Your Vision-Language Model Itself Is a Strong Filter: Towards High-Quality Instruction Tuning with Data SelectionCode1
A Critical Evaluation of AI Feedback for Aligning Large Language ModelsCode2
Language Models are Homer Simpson! Safety Re-Alignment of Fine-tuned Language Models through Task ArithmeticCode2
Transformer-based Causal Language Models Perform Clustering—0
EventRL: Enhancing Event Extraction with Outcome Supervision for Large Language ModelsCode3
Aligning Modalities in Vision Large Language Models via Preference Fine-tuningCode2
Aligning Large Language Models by On-Policy Self-JudgmentCode0
Multi-modal Preference Alignment Remedies Degradation of Visual Instruction Tuning on Language ModelsCode1
AbsInstruct: Eliciting Abstraction Ability from LLMs through Explanation Tuning with Plausibility EstimationCode0
Efficient Prompt Optimization Through the Lens of Best Arm Identification—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