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 111–120 of 1135 papers

TitleStatusHype
Efficient Telecom Specific LLM: TSLAM-Mini with QLoRA and Digital Twin Data—0
MM-Skin: Enhancing Dermatology Vision-Language Model with an Image-Text Dataset Derived from TextbooksCode1
Assessing Robustness to Spurious Correlations in Post-Training Language Models—0
Adaptive Markup Language Generation for Contextually-Grounded Visual Document UnderstandingCode1
T2VTextBench: A Human Evaluation Benchmark for Textual Control in Video Generation Models—0
Incentivizing Inclusive Contributions in Model Sharing Markets—0
LLaMA-Omni2: LLM-based Real-time Spoken Chatbot with Autoregressive Streaming Speech SynthesisCode3
PIPA: A Unified Evaluation Protocol for Diagnosing Interactive Planning Agents—0
T2VPhysBench: A First-Principles Benchmark for Physical Consistency in Text-to-Video Generation—0
UAV-VLN: End-to-End Vision Language guided Navigation for UAVs—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