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
Joint Flashback Adaptation for Forgetting-Resistant Instruction Tuning0
The Hidden Space of Safety: Understanding Preference-Tuned LLMs in Multilingual context0
KAUCUS: Knowledge Augmented User Simulators for Training Language Model Assistants0
Keypoints-Integrated Instruction-Following Data Generation for Enhanced Human Pose Understanding in Multimodal Models0
KITE: Keypoint-Conditioned Policies for Semantic Manipulation0
KIT's Offline Speech Translation and Instruction Following Submission for IWSLT 20250
KIWI: A Dataset of Knowledge-Intensive Writing Instructions for Answering Research Questions0
CROME: Cross-Modal Adapters for Efficient Multimodal LLM0
Knowledge-enhanced Agents for Interactive Text Games0
Kubrick: Multimodal Agent Collaborations for Synthetic Video Generation0
Mitigating Biases for Instruction-following Language Models via Bias Neurons Elimination0
Creating Arabic LLM Prompts at Scale0
LaMDAgent: An Autonomous Framework for Post-Training Pipeline Optimization via LLM Agents0
Language and Planning in Robotic Navigation: A Multilingual Evaluation of State-of-the-Art Models0
Language-Conditioned Goal Generation: a New Approach to Language Grounding for RL0
Language-Conditioned Goal Generation: a New Approach to Language Grounding in RL0
The Perfect Blend: Redefining RLHF with Mixture of Judges0
Language-guided Semantic Mapping and Mobile Manipulation in Partially Observable Environments0
Adaptive Decoding via Latent Preference Optimization0
Language Models are General-Purpose Interfaces0
CoTBal: Comprehensive Task Balancing for Multi-Task Visual Instruction Tuning0
COSMIC: Data Efficient Instruction-tuning For Speech In-Context Learning0
Language Models Benefit from Preparation with Elicited Knowledge0
AdaGrad under Anisotropic Smoothness0
Large Language Model as an Assignment Evaluator: Insights, Feedback, and Challenges in a 1000+ Student Course0
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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