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 151–175 of 1135 papers

TitleStatusHype
DrafterBench: Benchmarking Large Language Models for Tasks Automation in Civil EngineeringCode2
LLaSM: Large Language and Speech ModelCode2
LITA: Language Instructed Temporal-Localization AssistantCode2
ChartAssisstant: A Universal Chart Multimodal Language Model via Chart-to-Table Pre-training and Multitask Instruction TuningCode2
Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language ModelsCode2
Agentic Reward Modeling: Integrating Human Preferences with Verifiable Correctness Signals for Reliable Reward SystemsCode2
Draw-and-Understand: Leveraging Visual Prompts to Enable MLLMs to Comprehend What You WantCode2
DistiLLM-2: A Contrastive Approach Boosts the Distillation of LLMsCode2
LHRS-Bot-Nova: Improved Multimodal Large Language Model for Remote Sensing Vision-Language InterpretationCode2
Dual-Space Knowledge Distillation for Large Language ModelsCode2
F-LMM: Grounding Frozen Large Multimodal ModelsCode2
EarthGPT: A Universal Multi-modal Large Language Model for Multi-sensor Image Comprehension in Remote Sensing DomainCode2
AIR-Bench: Benchmarking Large Audio-Language Models via Generative ComprehensionCode2
EditWorld: Simulating World Dynamics for Instruction-Following Image EditingCode2
Archon: An Architecture Search Framework for Inference-Time TechniquesCode2
Direct Preference Optimization of Video Large Multimodal Models from Language Model RewardCode2
Learning to Decode Collaboratively with Multiple Language ModelsCode2
Lion: Adversarial Distillation of Proprietary Large Language ModelsCode2
LLaVA-MORE: A Comparative Study of LLMs and Visual Backbones for Enhanced Visual Instruction TuningCode2
LVLM-eHub: A Comprehensive Evaluation Benchmark for Large Vision-Language ModelsCode2
MentaLLaMA: Interpretable Mental Health Analysis on Social Media with Large Language ModelsCode2
DeSTA2.5-Audio: Toward General-Purpose Large Audio Language Model with Self-Generated Cross-Modal AlignmentCode2
Language Models are Homer Simpson! Safety Re-Alignment of Fine-tuned Language Models through Task ArithmeticCode2
DeSTA2: Developing Instruction-Following Speech Language Model Without Speech Instruction-Tuning DataCode2
Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free LunchCode2
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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