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 301–310 of 1135 papers

TitleStatusHype
LASeR: Learning to Adaptively Select Reward Models with Multi-Armed BanditsCode1
AlchemistCoder: Harmonizing and Eliciting Code Capability by Hindsight Tuning on Multi-source DataCode1
Language Imbalance Driven Rewarding for Multilingual Self-improvingCode1
Chat Vector: A Simple Approach to Equip LLMs with Instruction Following and Model Alignment in New LanguagesCode1
Language-Conditioned Reinforcement Learning to Solve Misunderstandings with Action CorrectionsCode1
Agri-LLaVA: Knowledge-Infused Large Multimodal Assistant on Agricultural Pests and DiseasesCode1
ChatGPT may Pass the Bar Exam soon, but has a Long Way to Go for the LexGLUE benchmarkCode1
AceGPT, Localizing Large Language Models in ArabicCode1
Lana: A Language-Capable Navigator for Instruction Following and GenerationCode1
Lexicon Learning for Few-Shot Neural Sequence ModelingCode1
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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