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 721–730 of 1135 papers

TitleStatusHype
Do LLMs estimate uncertainty well in instruction-following?Code0
Boosting LLM Translation Skills without General Ability Loss via Rationale Distillation—0
LoLDU: Low-Rank Adaptation via Lower-Diag-Upper Decomposition for Parameter-Efficient Fine-TuningCode0
Evaluating the Instruction-following Abilities of Language Models using Knowledge TasksCode0
POROver: Improving Safety and Reducing Overrefusal in Large Language Models with Overgeneration and Preference OptimizationCode0
SlideChat: A Large Vision-Language Assistant for Whole-Slide Pathology Image Understanding—0
Improving Instruction-Following in Language Models through Activation Steering—0
Speculative Knowledge Distillation: Bridging the Teacher-Student Gap Through Interleaved Sampling—0
ForgeryGPT: Multimodal Large Language Model For Explainable Image Forgery Detection and Localization—0
DrivingDojo Dataset: Advancing Interactive and Knowledge-Enriched Driving World Model—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