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 201250 of 1135 papers

TitleStatusHype
DistiLLM-2: A Contrastive Approach Boosts the Distillation of LLMsCode2
BLSP-Emo: Towards Empathetic Large Speech-Language ModelsCode2
LLM-RG4: Flexible and Factual Radiology Report Generation across Diverse Input ContextsCode2
MAPLM: A Real-World Large-Scale Vision-Language Benchmark for Map and Traffic Scene UnderstandingCode2
Autonomous Improvement of Instruction Following Skills via Foundation ModelsCode2
From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction TuningCode2
MMSci: A Dataset for Graduate-Level Multi-Discipline Multimodal Scientific UnderstandingCode2
Precise Zero-Shot Dense Retrieval without Relevance LabelsCode2
TimeChat: A Time-sensitive Multimodal Large Language Model for Long Video UnderstandingCode2
Beyond Task Performance: Evaluating and Reducing the Flaws of Large Multimodal Models with In-Context LearningCode1
Adaptive Markup Language Generation for Contextually-Grounded Visual Document UnderstandingCode1
LLaSA: A Multimodal LLM for Human Activity Analysis Through Wearable and Smartphone SensorsCode1
Hybrid Alignment Training for Large Language ModelsCode1
A Multi-Modal AI Copilot for Single-Cell Analysis with Instruction FollowingCode1
IDA-Bench: Evaluating LLMs on Interactive Guided Data AnalysisCode1
DISCO: Embodied Navigation and Interaction via Differentiable Scene Semantics and Dual-level ControlCode1
A Multi-Dimensional Constraint Framework for Evaluating and Improving Instruction Following in Large Language ModelsCode1
LLaMo: Large Language Model-based Molecular Graph AssistantCode1
BenchMAX: A Comprehensive Multilingual Evaluation Suite for Large Language ModelsCode1
Instruction Following without Instruction TuningCode1
Benchmarking Large Language Models on Controllable Generation under Diversified InstructionsCode1
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
Democratizing Reasoning Ability: Tailored Learning from Large Language ModelCode1
Defending Large Language Models against Jailbreak Attacks via Semantic SmoothingCode1
HalluciDoctor: Mitigating Hallucinatory Toxicity in Visual Instruction DataCode1
Defending Large Language Models Against Jailbreaking Attacks Through Goal PrioritizationCode1
DeCoRe: Decoding by Contrasting Retrieval Heads to Mitigate HallucinationsCode1
AlpaGasus: Training A Better Alpaca with Fewer DataCode1
Guiding Multi-Step Rearrangement Tasks with Natural Language InstructionsCode1
DANLI: Deliberative Agent for Following Natural Language InstructionsCode1
AlpaCare:Instruction-tuned Large Language Models for Medical ApplicationCode1
GIE-Bench: Towards Grounded Evaluation for Text-Guided Image EditingCode1
Demystifying Domain-adaptive Post-training for Financial LLMsCode1
LIONs: An Empirically Optimized Approach to Align Language ModelsCode1
Generation-driven Contrastive Self-training for Zero-shot Text Classification with Instruction-following LLMCode1
Curiosity-Driven Reinforcement Learning from Human FeedbackCode1
DialFRED: Dialogue-Enabled Agents for Embodied Instruction FollowingCode1
Generative Parameter-Efficient Fine-TuningCode1
AllenAct: A Framework for Embodied AI ResearchCode1
CrowdSelect: Synthetic Instruction Data Selection with Multi-LLM WisdomCode1
Bactrian-X: Multilingual Replicable Instruction-Following Models with Low-Rank AdaptationCode1
Lexicon Learning for Few-Shot Neural Sequence ModelingCode1
Cross-model Control: Improving Multiple Large Language Models in One-time TrainingCode1
Back to the Future: Towards Explainable Temporal Reasoning with Large Language ModelsCode1
Zero-Shot Compositional Policy Learning via Language GroundingCode1
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
LASeR: Learning to Adaptively Select Reward Models with Multi-Armed BanditsCode1
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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