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 481–490 of 1135 papers

TitleStatusHype
Improving Coherence and Consistency in Neural Sequence Models with Dual-System, Neuro-Symbolic Reasoning—0
Benchmarking and Improving Generator-Validator Consistency of Language Models—0
Alzheimer's Dementia Detection Using Perplexity from Paired Large Language Models—0
Adaptive Decoding via Latent Preference Optimization—0
Language-guided Semantic Mapping and Mobile Manipulation in Partially Observable Environments—0
Becoming self-instruct: introducing early stopping criteria for minimal instruct tuning—0
If You Can't Use Them, Recycle Them: Optimizing Merging at Scale Mitigates Performance Tradeoffs—0
Language-Conditioned Goal Generation: a New Approach to Language Grounding for RL—0
DecIF: Improving Instruction-Following through Meta-Decomposition—0
IFIR: A Comprehensive Benchmark for Evaluating Instruction-Following in Expert-Domain Information Retrieval—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