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 601–610 of 1135 papers

TitleStatusHype
Investigating Non-Transitivity in LLM-as-a-Judge—0
Instruction Tuning on Public Government and Cultural Data for Low-Resource Language: a Case Study in Kazakh—0
TALKPLAY: Multimodal Music Recommendation with Large Language Models—0
MMTEB: Massive Multilingual Text Embedding Benchmark—0
Integrating Arithmetic Learning Improves Mathematical Reasoning in Smaller Models—0
RoleMRC: A Fine-Grained Composite Benchmark for Role-Playing and Instruction-FollowingCode0
Learning to Keep a Promise: Scaling Language Model Decoding Parallelism with Learned Asynchronous Decoding—0
MuSC: Improving Complex Instruction Following with Multi-granularity Self-Contrastive TrainingCode0
SAIF: A Sparse Autoencoder Framework for Interpreting and Steering Instruction Following of Language Models—0
Do we Really Need Visual Instructions? Towards Visual Instruction-Free Fine-tuning for Large Vision-Language Models—0
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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