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 811–820 of 1135 papers

TitleStatusHype
Self-driven Grounding: Large Language Model Agents with Automatical Language-aligned Skill Learning—0
Self-Educated Language Agent with Hindsight Experience Replay for Instruction Following—0
HIGhER : Improving instruction following with Hindsight Generation for Experience Replay—0
VisualCritic: Making LMMs Perceive Visual Quality Like Humans—0
ARC: Argument Representation and Coverage Analysis for Zero-Shot Long Document Summarization with Instruction Following LLMs—0
Visual Fact Checker: Enabling High-Fidelity Detailed Caption Generation—0
AnyCap Project: A Unified Framework, Dataset, and Benchmark for Controllable Omni-modal Captioning—0
An Incomplete Loop: Deductive, Inductive, and Abductive Learning in Large Language Models—0
When Thinking Fails: The Pitfalls of Reasoning for Instruction-Following in LLMs—0
Self-Specialization: Uncovering Latent Expertise within 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