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 526–550 of 1135 papers

TitleStatusHype
From Loops to Oops: Fallback Behaviors of Language Models Under UncertaintyCode0
Large Language Model as an Assignment Evaluator: Insights, Feedback, and Challenges in a 1000+ Student Course—0
MMSci: A Dataset for Graduate-Level Multi-Discipline Multimodal Scientific UnderstandingCode2
Me, Myself, and AI: The Situational Awareness Dataset (SAD) for LLMsCode1
Semantic Graphs for Syntactic Simplification: A Revisit from the Age of LLMCode0
Benchmarking Complex Instruction-Following with Multiple Constraints CompositionCode2
FunAudioLLM: Voice Understanding and Generation Foundation Models for Natural Interaction Between Humans and LLMsCode11
Diverse and Fine-Grained Instruction-Following Ability Exploration with Synthetic Data—0
Pelican: Correcting Hallucination in Vision-LLMs via Claim Decomposition and Program of Thought Verification—0
D-Rax: Domain-specific Radiologic assistant leveraging multi-modal data and eXpert model predictions—0
MIA-Bench: Towards Better Instruction Following Evaluation of Multimodal LLMsCode1
Improving Multilingual Instruction Finetuning via Linguistically Natural and Diverse Datasets—0
Iterative Data Generation with Large Language Models for Aspect-based Sentiment Analysis—0
The SIFo Benchmark: Investigating the Sequential Instruction Following Ability of Large Language ModelsCode1
ScaleBiO: Scalable Bilevel Optimization for LLM Data Reweighting—0
MM-Instruct: Generated Visual Instructions for Large Multimodal Model AlignmentCode1
OmniJARVIS: Unified Vision-Language-Action Tokenization Enables Open-World Instruction Following Agents—0
LiveBench: A Challenging, Contamination-Limited LLM BenchmarkCode5
DeSTA: Enhancing Speech Language Models through Descriptive Speech-Text Alignment—0
Suri: Multi-constraint Instruction Following for Long-form Text GenerationCode1
Role-Play Zero-Shot Prompting with Large Language Models for Open-Domain Human-Machine Conversation—0
A Text is Worth Several Tokens: Text Embedding from LLMs Secretly Aligns Well with The Key Tokens—0
Following Length Constraints in Instructions—0
Dual-Space Knowledge Distillation for Large Language ModelsCode2
AutoDetect: Towards a Unified Framework for Automated Weakness Detection in Large Language ModelsCode1
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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