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 1121–1130 of 1135 papers

TitleStatusHype
LLM Self-Correction with DeCRIM: Decompose, Critique, and Refine for Enhanced Following of Instructions with Multiple Constraints—0
LLMs for Generalizable Language-Conditioned Policy Learning under Minimal Data Requirements—0
CMI-Bench: A Comprehensive Benchmark for Evaluating Music Instruction Following—0
Closed-Loop Open-Vocabulary Mobile Manipulation with GPT-4V—0
CLIP-Nav: Using CLIP for Zero-Shot Vision-and-Language Navigation—0
LoGra-Med: Long Context Multi-Graph Alignment for Medical Vision-Language Model—0
LoHoRavens: A Long-Horizon Language-Conditioned Benchmark for Robotic Tabletop Manipulation—0
clembench-2024: A Challenging, Dynamic, Complementary, Multilingual Benchmark and Underlying Flexible Framework for LLMs as Multi-Action Agents—0
Long Context Alignment with Short Instructions and Synthesized Positions—0
CIF-Bench: A Chinese Instruction-Following Benchmark for Evaluating the Generalizability of 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