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

Showing 251260 of 1135 papers

TitleStatusHype
Aya Dataset: An Open-Access Collection for Multilingual Instruction TuningCode1
Creative Agents: Empowering Agents with Imagination for Creative TasksCode1
Counterfactual Cycle-Consistent Learning for Instruction Following and Generation in Vision-Language NavigationCode1
Beyond Task Performance: Evaluating and Reducing the Flaws of Large Multimodal Models with In-Context LearningCode1
Generative Parameter-Efficient Fine-TuningCode1
LIONs: An Empirically Optimized Approach to Align Language ModelsCode1
Learning to Map Natural Language Instructions to Physical Quadcopter Control using Simulated FlightCode1
CoPESD: A Multi-Level Surgical Motion Dataset for Training Large Vision-Language Models to Co-Pilot Endoscopic Submucosal DissectionCode1
CoachLM: Automatic Instruction Revisions Improve the Data Quality in LLM Instruction TuningCode1
Contrastive Vision-Language Alignment Makes Efficient Instruction LearnerCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AutoIF (Llama3 70B)Inst-level loose-accuracy90.4Unverified
2AutoIF (Qwen2 72B)Inst-level loose-accuracy88Unverified
3GPT-4Inst-level loose-accuracy85.37Unverified
4PaLM 2 SInst-level loose-accuracy59.11Unverified