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 276–300 of 1135 papers

TitleStatusHype
Investigating the Effectiveness of Task-Agnostic Prefix Prompt for Instruction FollowingCode1
Inferring Rewards from Language in ContextCode1
Aligning Instruction Tasks Unlocks Large Language Models as Zero-Shot Relation ExtractorsCode1
AutoDetect: Towards a Unified Framework for Automated Weakness Detection in Large Language ModelsCode1
MathChat: Benchmarking Mathematical Reasoning and Instruction Following in Multi-Turn InteractionsCode1
Context-Aware Planning and Environment-Aware Memory for Instruction Following Embodied AgentsCode1
Constraint Back-translation Improves Complex Instruction Following of Large Language ModelsCode1
InfMLLM: A Unified Framework for Visual-Language TasksCode1
Improving Translation Faithfulness of Large Language Models via Augmenting InstructionsCode1
Lana: A Language-Capable Navigator for Instruction Following and GenerationCode1
MedQA-CS: Benchmarking Large Language Models Clinical Skills Using an AI-SCE FrameworkCode1
Hybrid Alignment Training for Large Language ModelsCode1
Lottery Ticket Adaptation: Mitigating Destructive Interference in LLMsCode1
IDA-Bench: Evaluating LLMs on Interactive Guided Data AnalysisCode1
Lumen: Unleashing Versatile Vision-Centric Capabilities of Large Multimodal ModelsCode1
LoGU: Long-form Generation with Uncertainty ExpressionsCode1
Combining Modular Skills in Multitask LearningCode1
Unlocking Reasoning Potential in Large Langauge Models by Scaling Code-form PlanningCode1
LLMs Are Biased Towards Output Formats! Systematically Evaluating and Mitigating Output Format Bias of LLMsCode1
CodeIF: Benchmarking the Instruction-Following Capabilities of Large Language Models for Code GenerationCode1
ChemEval: A Comprehensive Multi-Level Chemical Evaluation for Large Language ModelsCode1
M3DBench: Let's Instruct Large Models with Multi-modal 3D PromptsCode1
A Survey on Data Selection for LLM Instruction TuningCode1
Guiding Multi-Step Rearrangement Tasks with Natural Language InstructionsCode1
Alexa Arena: A User-Centric Interactive Platform for Embodied AICode1
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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