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

Showing 551575 of 1135 papers

TitleStatusHype
FollowEval: A Multi-Dimensional Benchmark for Assessing the Instruction-Following Capability of Large Language Models0
StyleAR: Customizing Multimodal Autoregressive Model for Style-Aligned Text-to-Image Generation0
Following Instructions by Imagining and Reaching Visual Goals0
Following Length Constraints in Instructions0
Summarizing a virtual robot's past actions in natural language0
ForgeryGPT: Multimodal Large Language Model For Explainable Image Forgery Detection and Localization0
Foundational Model for Electron Micrograph Analysis: Instruction-Tuning Small-Scale Language-and-Vision Assistant for Enterprise Adoption0
Fox-1 Technical Report0
From 128K to 4M: Efficient Training of Ultra-Long Context Large Language Models0
From Alignment to Advancement: Bootstrapping Audio-Language Alignment with Synthetic Data0
From “Before” to “After”: Generating Natural Language Instructions from Image Pairs in a Simple Visual Domain0
Superficial Safety Alignment Hypothesis0
From Language to Goals: Inverse Reinforcement Learning for Vision-Based Instruction Following0
From Persona to Personalization: A Survey on Role-Playing Language Agents0
Surgical-LLaVA: Toward Surgical Scenario Understanding via Large Language and Vision Models0
From Role-Play to Drama-Interaction: An LLM Solution0
From Words to Workflows: Automating Business Processes0
Frustrated with Code Quality Issues? LLMs can Help!0
Who Taught You That? Tracing Teachers in Model Distillation0
DNA 1.0 Technical Report0
Diversity Measurement and Subset Selection for Instruction Tuning Datasets0
Gaining Wisdom from Setbacks: Aligning Large Language Models via Mistake Analysis0
Diverse and Fine-Grained Instruction-Following Ability Exploration with Synthetic Data0
Gaussian Scenes: Pose-Free Sparse-View Scene Reconstruction using Depth-Enhanced Diffusion Priors0
Gemma 3 Technical Report0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AutoIF (Llama3 70B)Inst-level loose-accuracy90.4Unverified
2AutoIF (Qwen2 72B)Inst-level loose-accuracy88Unverified
3GPT-4Inst-level loose-accuracy85.37Unverified
4PaLM 2 SInst-level loose-accuracy59.11Unverified