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 971–980 of 1135 papers

TitleStatusHype
Self-Corrected Multimodal Large Language Model for End-to-End Robot Manipulation—0
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
Identifying Reliable Evaluation Metrics for Scientific Text RevisionCode0
Building Accurate Translation-Tailored LLMs with Language Aware Instruction TuningCode0
ASMA-Tune: Unlocking LLMs' Assembly Code Comprehension via Structural-Semantic Instruction TuningCode0
IFShip: Interpretable Fine-grained Ship Classification with Domain Knowledge-Enhanced Vision-Language ModelsCode0
CommonIT: Commonality-Aware Instruction Tuning for Large Language Models via Data PartitionsCode0
PACIT: Unlocking the Power of Examples for Better In-Context Instruction TuningCode0
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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