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 576–600 of 1135 papers

TitleStatusHype
How Far Can In-Context Alignment Go? Exploring the State of In-Context Alignment—0
WPO: Enhancing RLHF with Weighted Preference OptimizationCode1
GAMA: A Large Audio-Language Model with Advanced Audio Understanding and Complex Reasoning AbilitiesCode2
Refusal in Language Models Is Mediated by a Single DirectionCode3
Embodied Instruction Following in Unknown Environments—0
Reminding Multimodal Large Language Models of Object-aware Knowledge with Retrieved Tags—0
DiscreteSLU: A Large Language Model with Self-Supervised Discrete Speech Units for Spoken Language Understanding—0
Unpacking DPO and PPO: Disentangling Best Practices for Learning from Preference FeedbackCode7
MiLoRA: Harnessing Minor Singular Components for Parameter-Efficient LLM FinetuningCode3
Comparison Visual Instruction Tuning—0
Mimicking User Data: On Mitigating Fine-Tuning Risks in Closed Large Language Models—0
TasTe: Teaching Large Language Models to Translate through Self-ReflectionCode1
OPTune: Efficient Online Preference Tuning—0
CoEvol: Constructing Better Responses for Instruction Finetuning through Multi-Agent CooperationCode0
3D-Properties: Identifying Challenges in DPO and Charting a Path Forward—0
FaceGPT: Self-supervised Learning to Chat about 3D Human Faces—0
RS-Agent: Automating Remote Sensing Tasks through Intelligent AgentCode2
SciRIFF: A Resource to Enhance Language Model Instruction-Following over Scientific LiteratureCode1
The BiGGen Bench: A Principled Benchmark for Fine-grained Evaluation of Language Models with Language ModelsCode5
F-LMM: Grounding Frozen Large Multimodal ModelsCode2
CorDA: Context-Oriented Decomposition Adaptation of Large Language Models for Task-Aware Parameter-Efficient Fine-tuningCode2
GenAI Arena: An Open Evaluation Platform for Generative ModelsCode2
BLSP-Emo: Towards Empathetic Large Speech-Language ModelsCode2
Synthetic Programming Elicitation for Text-to-Code in Very Low-Resource Programming and Formal LanguagesCode0
Large Language Models as Evaluators for Recommendation ExplanationsCode1
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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