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 561–570 of 1135 papers

TitleStatusHype
LLaSA: A Multimodal LLM for Human Activity Analysis Through Wearable and Smartphone SensorsCode1
IWISDM: Assessing instruction following in multimodal models at scaleCode0
Finding Blind Spots in Evaluator LLMs with Interpretable ChecklistsCode1
Biomedical Visual Instruction Tuning with Clinician Preference AlignmentCode0
Self-play with Execution Feedback: Improving Instruction-following Capabilities of Large Language ModelsCode3
The Comparative Trap: Pairwise Comparisons Amplifies Biased Preferences of LLM Evaluators—0
Unveiling the Flaws: Exploring Imperfections in Synthetic Data and Mitigation Strategies for Large Language Models—0
ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All ToolsCode14
Opt-Out: Investigating Entity-Level Unlearning for Large Language Models via Optimal TransportCode0
RS-GPT4V: A Unified Multimodal Instruction-Following Dataset for Remote Sensing Image UnderstandingCode1
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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