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 621–630 of 1135 papers

TitleStatusHype
Improving Coherence and Consistency in Neural Sequence Models with Dual-System, Neuro-Symbolic Reasoning—0
Improving Instruction-Following in Language Models through Activation Steering—0
Improving Instruct Models for Free: A Study on Partial Adaptation—0
Improving Multilingual Instruction Finetuning via Linguistically Natural and Diverse Datasets—0
Improving Open Information Extraction with Large Language Models: A Study on Demonstration Uncertainty—0
Improving Reward Models with Synthetic Critiques—0
Improving the Robustness of Large Language Models via Consistency Alignment—0
Improving the Robustness to Variations of Objects and Instructions with a Neuro-Symbolic Approach for Interactive Instruction Following—0
Incentivizing Inclusive Contributions in Model Sharing Markets—0
TALKPLAY: Multimodal Music Recommendation with Large Language 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