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 241–250 of 1135 papers

TitleStatusHype
Training an LLM-as-a-Judge Model: Pipeline, Insights, and Practical Lessons—0
SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model—0
Shuttle Between the Instructions and the Parameters of Large Language Models—0
CoDe: Blockwise Control for Denoising Diffusion ModelsCode0
BARE: Leveraging Base Language Models for Few-Shot Synthetic Data Generation—0
Learning Human Perception Dynamics for Informative Robot Communication—0
Disentangling Length Bias In Preference Learning Via Response-Conditioned Modeling—0
ReFoRCE: A Text-to-SQL Agent with Self-Refinement, Format Restriction, and Column Exploration—0
mFollowIR: a Multilingual Benchmark for Instruction Following in RetrievalCode2
Rethinking Bottlenecks in Safety Fine-Tuning of Vision 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