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 131–140 of 1135 papers

TitleStatusHype
OmniBench: Towards The Future of Universal Omni-Language ModelsCode2
DistiLLM-2: A Contrastive Approach Boosts the Distillation of LLMsCode2
Diffusion-ES: Gradient-free Planning with Diffusion for Autonomous Driving and Zero-Shot Instruction FollowingCode2
Direct Preference Optimization of Video Large Multimodal Models from Language Model RewardCode2
DeSTA2.5-Audio: Toward General-Purpose Large Audio Language Model with Self-Generated Cross-Modal AlignmentCode2
DeSTA2: Developing Instruction-Following Speech Language Model Without Speech Instruction-Tuning DataCode2
Asynchronous RLHF: Faster and More Efficient Off-Policy RL for Language ModelsCode2
Learning to Decode Collaboratively with Multiple Language ModelsCode2
Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free LunchCode2
Language Models are Homer Simpson! Safety Re-Alignment of Fine-tuned Language Models through Task ArithmeticCode2
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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