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 181–190 of 1135 papers

TitleStatusHype
Implicit Cross-Lingual Rewarding for Efficient Multilingual Preference AlignmentCode0
FuseChat-3.0: Preference Optimization Meets Heterogeneous Model FusionCode1
IFIR: A Comprehensive Benchmark for Evaluating Instruction-Following in Expert-Domain Information Retrieval—0
CodeIF-Bench: Evaluating Instruction-Following Capabilities of Large Language Models in Interactive Code Generation—0
LEWIS (LayEr WIse Sparsity) -- A Training Free Guided Model Merging Approach—0
Unified Mind Model: Reimagining Autonomous Agents in the LLM Era—0
Attentive Reasoning Queries: A Systematic Method for Optimizing Instruction-Following in Large Language ModelsCode11
Robust Learning of Diverse Code Edits—0
Iterative Value Function Optimization for Guided Decoding—0
InSerter: Speech Instruction Following with Unsupervised Interleaved Pre-training—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