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 26–50 of 1135 papers

TitleStatusHype
Aria: An Open Multimodal Native Mixture-of-Experts ModelCode5
Jamba-1.5: Hybrid Transformer-Mamba Models at ScaleCode5
LiveBench: A Challenging, Contamination-Limited LLM BenchmarkCode5
The BiGGen Bench: A Principled Benchmark for Fine-grained Evaluation of Language Models with Language ModelsCode5
LAB: Large-Scale Alignment for ChatBotsCode5
Ranni: Taming Text-to-Image Diffusion for Accurate Instruction FollowingCode5
Instruction-Following Evaluation for Large Language ModelsCode5
ImageBind-LLM: Multi-modality Instruction TuningCode5
MMBench: Is Your Multi-modal Model an All-around Player?Code5
LLaMA-Adapter V2: Parameter-Efficient Visual Instruction ModelCode5
WizardLM: Empowering Large Language Models to Follow Complex InstructionsCode5
Towards Better Instruction Following Language Models for Chinese: Investigating the Impact of Training Data and EvaluationCode5
LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init AttentionCode5
Self-Instruct: Aligning Language Models with Self-Generated InstructionsCode5
Kwai Keye-VL Technical ReportCode4
RewardBench 2: Advancing Reward Model EvaluationCode4
Parameter Efficient Instruction Tuning: An Empirical StudyCode4
FuseChat: Knowledge Fusion of Chat ModelsCode4
PromptFix: You Prompt and We Fix the PhotoCode4
A Survey on Vision-Language-Action Models for Embodied AICode4
SimPO: Simple Preference Optimization with a Reference-Free RewardCode4
RewardBench: Evaluating Reward Models for Language ModelingCode4
LLaMA Pro: Progressive LLaMA with Block ExpansionCode4
AgentBench: Evaluating LLMs as AgentsCode4
How Far Can Camels Go? Exploring the State of Instruction Tuning on Open ResourcesCode4
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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