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 676700 of 1135 papers

TitleStatusHype
Compositional Image Retrieval via Instruction-Aware Contrastive LearningCode0
LLM-Align: Utilizing Large Language Models for Entity Alignment in Knowledge Graphs0
EXAONE 3.5: Series of Large Language Models for Real-world Use Cases0
If You Can't Use Them, Recycle Them: Optimizing Merging at Scale Mitigates Performance Tradeoffs0
VidHalluc: Evaluating Temporal Hallucinations in Multimodal Large Language Models for Video Understanding0
From Words to Workflows: Automating Business Processes0
Optimizing Latent Goal by Learning from Trajectory Preference0
T-REG: Preference Optimization with Token-Level Reward RegularizationCode0
Enhancing Function-Calling Capabilities in LLMs: Strategies for Prompt Formats, Data Integration, and Multilingual Translation0
AlignFormer: Modality Matching Can Achieve Better Zero-shot Instruction-Following Speech-LLM0
MiningGPT -- A Domain-Specific Large Language Model for the Mining Industry0
VISTA: Enhancing Long-Duration and High-Resolution Video Understanding by Video Spatiotemporal Augmentation0
InsightEdit: Towards Better Instruction Following for Image Editing0
Gaussian Scenes: Pose-Free Sparse-View Scene Reconstruction using Depth-Enhanced Diffusion Priors0
From MTEB to MTOB: Retrieval-Augmented Classification for Descriptive GrammarsCode0
Enhancing Instruction-Following Capability of Visual-Language Models by Reducing Image Redundancy0
Separable Mixture of Low-Rank Adaptation for Continual Visual Instruction Tuning0
MpoxVLM: A Vision-Language Model for Diagnosing Skin Lesions from Mpox Virus InfectionCode0
MLAN: Language-Based Instruction Tuning Improves Zero-Shot Generalization of Multimodal Large Language ModelsCode0
Adaptive Decoding via Latent Preference Optimization0
Zero-shot Object-Centric Instruction Following: Integrating Foundation Models with Traditional Navigation0
Stronger Models are NOT Stronger Teachers for Instruction Tuning0
MrSteve: Instruction-Following Agents in Minecraft with What-Where-When Memory0
LIFBench: Evaluating the Instruction Following Performance and Stability of Large Language Models in Long-Context ScenariosCode0
IOPO: Empowering LLMs with Complex Instruction Following via Input-Output Preference Optimization0
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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