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 101125 of 1135 papers

TitleStatusHype
LLark: A Multimodal Instruction-Following Language Model for MusicCode2
LLaVAR: Enhanced Visual Instruction Tuning for Text-Rich Image UnderstandingCode2
MentaLLaMA: Interpretable Mental Health Analysis on Social Media with Large Language ModelsCode2
LITA: Language Instructed Temporal-Localization AssistantCode2
LHRS-Bot-Nova: Improved Multimodal Large Language Model for Remote Sensing Vision-Language InterpretationCode2
Lion: Adversarial Distillation of Proprietary Large Language ModelsCode2
Learning to Decode Collaboratively with Multiple Language ModelsCode2
DrafterBench: Benchmarking Large Language Models for Tasks Automation in Civil EngineeringCode2
Autonomous Improvement of Instruction Following Skills via Foundation ModelsCode2
CoIN: A Benchmark of Continual Instruction tuNing for Multimodel Large Language ModelCode2
Aligning Modalities in Vision Large Language Models via Preference Fine-tuningCode2
BayLing: Bridging Cross-lingual Alignment and Instruction Following through Interactive Translation for Large Language ModelsCode2
DistiLLM-2: A Contrastive Approach Boosts the Distillation of LLMsCode2
A Critical Evaluation of AI Feedback for Aligning Large Language ModelsCode2
Conifer: Improving Complex Constrained Instruction-Following Ability of Large Language ModelsCode2
Benchmarking Complex Instruction-Following with Multiple Constraints CompositionCode2
Language Models are Homer Simpson! Safety Re-Alignment of Fine-tuned Language Models through Task ArithmeticCode2
Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free LunchCode2
Draw-and-Understand: Leveraging Visual Prompts to Enable MLLMs to Comprehend What You WantCode2
EditWorld: Simulating World Dynamics for Instruction-Following Image EditingCode2
AutoDefense: Multi-Agent LLM Defense against Jailbreak AttacksCode2
LM-Nav: Robotic Navigation with Large Pre-Trained Models of Language, Vision, and ActionCode2
EmoLLMs: A Series of Emotional Large Language Models and Annotation Tools for Comprehensive Affective AnalysisCode2
Long-Context Language Modeling with Parallel Context EncodingCode2
Aurora:Activating Chinese chat capability for Mixtral-8x7B sparse Mixture-of-Experts through Instruction-TuningCode2
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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