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 541–550 of 1135 papers

TitleStatusHype
ParamΔ for Direct Weight Mixing: Post-Train Large Language Model at Zero Cost—0
Case Study: Fine-tuning Small Language Models for Accurate and Private CWE Detection in Python Code—0
DistilQwen2.5: Industrial Practices of Training Distilled Open Lightweight Language Models—0
Evaluating Judges as Evaluators: The JETTS Benchmark of LLM-as-Judges as Test-Time Scaling EvaluatorsCode0
Improving Instruct Models for Free: A Study on Partial Adaptation—0
SIFT-50M: A Large-Scale Multilingual Dataset for Speech Instruction Fine-Tuning—0
Playpen: An Environment for Exploring Learning Through Conversational InteractionCode0
VideoExpert: Augmented LLM for Temporal-Sensitive Video Understanding—0
Capybara-OMNI: An Efficient Paradigm for Building Omni-Modal Language Models—0
Holistic Capability Preservation: Towards Compact Yet Comprehensive Reasoning Models—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