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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 951–975 of 1135 papers

TitleStatusHype
Diffusion vs. Autoregressive Language Models: A Text Embedding Perspective—0
Grounding Language by Continuous Observation of Instruction Following—0
Language Conditioned Imitation Learning over Unstructured Data—0
Ground-level Viewpoint Vision-and-Language Navigation in Continuous Environments—0
Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels—0
Guided Adaptive Credit Assignment for Sample Efficient Policy Optimization—0
Differential Information: An Information-Theoretic Perspective on Preference Optimization—0
Systematic Evaluation of Long-Context LLMs on Financial Concepts—0
HAPFI: History-Aware Planning based on Fused Information—0
DiffChat: Learning to Chat with Text-to-Image Synthesis Models for Interactive Image Creation—0
SteP: Stacked LLM Policies for Web Actions—0
HELPER-X: A Unified Instructable Embodied Agent to Tackle Four Interactive Vision-Language Domains with Memory-Augmented Language Models—0
HERM: Benchmarking and Enhancing Multimodal LLMs for Human-Centric Understanding—0
Procedures as Programs: Hierarchical Control of Situated Agents through Natural Language—0
Hindsight Planner: A Closed-Loop Few-Shot Planner for Embodied Instruction Following—0
Hi Robot: Open-Ended Instruction Following with Hierarchical Vision-Language-Action Models—0
Holistic Capability Preservation: Towards Compact Yet Comprehensive Reasoning Models—0
DeSTA: Enhancing Speech Language Models through Descriptive Speech-Text Alignment—0
DEM: Distribution Edited Model for Training with Mixed Data Distributions—0
How Far Can In-Context Alignment Go? Exploring the State of In-Context Alignment—0
DecIF: Improving Instruction-Following through Meta-Decomposition—0
How Many Instructions Can LLMs Follow at Once?—0
How well can LLMs Grade Essays in Arabic?—0
Human Instruction-Following with Deep Reinforcement Learning via Transfer-Learning from Text—0
HSI-GPT: A General-Purpose Large Scene-Motion-Language Model for Human Scene Interaction—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