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

Showing 521530 of 1135 papers

TitleStatusHype
Empowering Persian LLMs for Instruction Following: A Novel Dataset and Training ApproachCode0
Instruction Following with Goal-Conditioned Reinforcement Learning in Virtual EnvironmentsCode0
Beyond Instruction Following: Evaluating Inferential Rule Following of Large Language Models0
LIONs: An Empirically Optimized Approach to Align Language ModelsCode1
LVLM-empowered Multi-modal Representation Learning for Visual Place Recognition0
From Loops to Oops: Fallback Behaviors of Language Models Under UncertaintyCode0
Large Language Model as an Assignment Evaluator: Insights, Feedback, and Challenges in a 1000+ Student Course0
MMSci: A Dataset for Graduate-Level Multi-Discipline Multimodal Scientific UnderstandingCode2
Me, Myself, and AI: The Situational Awareness Dataset (SAD) for LLMsCode1
Semantic Graphs for Syntactic Simplification: A Revisit from the Age of LLMCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AutoIF (Llama3 70B)Inst-level loose-accuracy90.4Unverified
2AutoIF (Qwen2 72B)Inst-level loose-accuracy88Unverified
3GPT-4Inst-level loose-accuracy85.37Unverified
4PaLM 2 SInst-level loose-accuracy59.11Unverified