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 221–230 of 1135 papers

TitleStatusHype
Benchmarking Generation and Evaluation Capabilities of Large Language Models for Instruction Controllable SummarizationCode1
A modular vision language navigation and manipulation framework for long horizon compositional tasks in indoor environmentCode1
Lana: A Language-Capable Navigator for Instruction Following and GenerationCode1
AlpaGasus: Training A Better Alpaca with Fewer DataCode1
Language-Conditioned Reinforcement Learning to Solve Misunderstandings with Action CorrectionsCode1
KaSA: Knowledge-Aware Singular-Value Adaptation of Large Language ModelsCode1
DANLI: Deliberative Agent for Following Natural Language InstructionsCode1
AlpaCare:Instruction-tuned Large Language Models for Medical ApplicationCode1
DeCoRe: Decoding by Contrasting Retrieval Heads to Mitigate HallucinationsCode1
GIE-Bench: Towards Grounded Evaluation for Text-Guided Image EditingCode1
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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