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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 351–375 of 1135 papers

TitleStatusHype
DocLens: Multi-aspect Fine-grained Evaluation for Medical Text GenerationCode1
Lexicon Learning for Few Shot Sequence ModelingCode1
Learning to Map Natural Language Instructions to Physical Quadcopter Control using Simulated FlightCode1
Enhancing Cross-Tokenizer Knowledge Distillation with Contextual Dynamical MappingCode1
CB2: Collaborative Natural Language Interaction Research PlatformCode1
Engineering flexible machine learning systems by traversing functionally-invariant pathsCode1
Large Language Models as Evaluators for Recommendation ExplanationsCode1
Are Emergent Abilities in Large Language Models just In-Context Learning?Code1
LASeR: Learning to Adaptively Select Reward Models with Multi-Armed BanditsCode1
MergeBench: A Benchmark for Merging Domain-Specialized LLMsCode1
Unlocking Reasoning Potential in Large Langauge Models by Scaling Code-form PlanningCode1
Follow My Instruction and Spill the Beans: Scalable Data Extraction from Retrieval-Augmented Generation SystemsCode1
Lana: A Language-Capable Navigator for Instruction Following and GenerationCode1
MoDS: Model-oriented Data Selection for Instruction TuningCode1
A Recipe For Building a Compliant Real Estate ChatbotCode1
Cappy: Outperforming and Boosting Large Multi-Task LMs with a Small ScorerCode1
Language-Conditioned Reinforcement Learning to Solve Misunderstandings with Action CorrectionsCode1
Adversarial Paraphrasing: A Universal Attack for Humanizing AI-Generated TextCode1
Efficient Inference of Vision Instruction-Following Models with Elastic CacheCode1
FuseChat-3.0: Preference Optimization Meets Heterogeneous Model FusionCode1
Kun: Answer Polishment for Chinese Self-Alignment with Instruction Back-TranslationCode1
Language Imbalance Driven Rewarding for Multilingual Self-improvingCode1
LLaSA: A Multimodal LLM for Human Activity Analysis Through Wearable and Smartphone SensorsCode1
Can Language Models Follow Multiple Turns of Entangled Instructions?Code1
Is In-Context Learning Sufficient for Instruction Following in LLMs?Code1
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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