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 861–870 of 1135 papers

TitleStatusHype
Emo-DPO: Controllable Emotional Speech Synthesis through Direct Preference Optimization—0
D-Rax: Domain-specific Radiologic assistant leveraging multi-modal data and eXpert model predictions—0
Empirical Analysis of Large Vision-Language Models against Goal Hijacking via Visual Prompt Injection—0
Empowering LLMs to Understand and Generate Complex Vector Graphics—0
Draw Me a Flower: Processing and Grounding Abstraction in Natural Language—0
Enabling High-Sparsity Foundational Llama Models with Efficient Pretraining and Deployment—0
VL-Trojan: Multimodal Instruction Backdoor Attacks against Autoregressive Visual Language Models—0
Enhancing Complex Instruction Following for Large Language Models with Mixture-of-Contexts Fine-tuning—0
Enhancing Function-Calling Capabilities in LLMs: Strategies for Prompt Formats, Data Integration, and Multilingual Translation—0
Enhancing Instruction-Following Capability of Visual-Language Models by Reducing Image Redundancy—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