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 231–240 of 1135 papers

TitleStatusHype
STING-BEE: Towards Vision-Language Model for Real-World X-ray Baggage Security InspectionCode1
InsViE-1M: Effective Instruction-based Video Editing with Elaborate Dataset ConstructionCode1
Can Language Models Follow Multiple Turns of Entangled Instructions?Code1
REF-VLM: Triplet-Based Referring Paradigm for Unified Visual DecodingCode1
FuseChat-3.0: Preference Optimization Meets Heterogeneous Model FusionCode1
CrowdSelect: Synthetic Instruction Data Selection with Multi-LLM WisdomCode1
CodeIF: Benchmarking the Instruction-Following Capabilities of Large Language Models for Code GenerationCode1
StructFlowBench: A Structured Flow Benchmark for Multi-turn Instruction FollowingCode1
Enhancing Cross-Tokenizer Knowledge Distillation with Contextual Dynamical MappingCode1
IHEval: Evaluating Language Models on Following the Instruction HierarchyCode1
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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