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 591–600 of 1135 papers

TitleStatusHype
Opt-Out: Investigating Entity-Level Unlearning for Large Language Models via Optimal TransportCode0
Hierarchical Modular Framework for Long Horizon Instruction FollowingCode0
Rate, Explain and Cite (REC): Enhanced Explanation and Attribution in Automatic Evaluation by Large Language ModelsCode0
Alignment-based compositional semantics for instruction followingCode0
Align^2LLaVA: Cascaded Human and Large Language Model Preference Alignment for Multi-modal Instruction CurationCode0
DialMAT: Dialogue-Enabled Transformer with Moment-Based Adversarial TrainingCode0
Compositional Image Retrieval via Instruction-Aware Contrastive LearningCode0
SOTOPIA-Ω: Dynamic Strategy Injection Learning and Social Instruction Following Evaluation for Social AgentsCode0
Implicit Cross-Lingual Rewarding for Efficient Multilingual Preference AlignmentCode0
Mapping Instructions to Actions in 3D Environments with Visual Goal PredictionCode0
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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