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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 581–590 of 1135 papers

TitleStatusHype
Synthetic Programming Elicitation for Text-to-Code in Very Low-Resource Programming and Formal LanguagesCode0
Guiding Policies with Language via Meta-LearningCode0
Token-Efficient Leverage Learning in Large Language ModelsCode0
HalLoc: Token-level Localization of Hallucinations for Vision Language ModelsCode0
LIFBench: Evaluating the Instruction Following Performance and Stability of Large Language Models in Long-Context ScenariosCode0
LIFEBench: Evaluating Length Instruction Following in Large Language ModelsCode0
Sloth: scaling laws for LLM skills to predict multi-benchmark performance across familiesCode0
IndiVec: An Exploration of Leveraging Large Language Models for Media Bias Detection with Fine-Grained Bias IndicatorsCode0
Automated curriculum generation for Policy Gradients from DemonstrationsCode0
Iterative Label Refinement Matters More than Preference Optimization under Weak SupervisionCode0
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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