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 931–940 of 1135 papers

TitleStatusHype
X-Shot: A Unified System to Handle Frequent, Few-shot and Zero-shot Learning Simultaneously in ClassificationCode0
CoGenesis: A Framework Collaborating Large and Small Language Models for Secure Context-Aware Instruction Following—0
OPEx: A Component-Wise Analysis of LLM-Centric Agents in Embodied Instruction Following—0
Collaborative decoding of critical tokens for boosting factuality of large language models—0
Think Big, Generate Quick: LLM-to-SLM for Fast Autoregressive Decoding—0
NaVid: Video-based VLM Plans the Next Step for Vision-and-Language Navigation—0
Towards Robust Instruction Tuning on Multimodal Large Language ModelsCode0
Zero-shot cross-lingual transfer in instruction tuning of large language models—0
Unintended Impacts of LLM Alignment on Global RepresentationCode0
Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking—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