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 526–550 of 1135 papers

TitleStatusHype
How Far Can In-Context Alignment Go? Exploring the State of In-Context Alignment—0
Balancing Continuous Pre-Training and Instruction Fine-Tuning: Optimizing Instruction-Following in LLMs—0
HelpSteer3-Preference: Open Human-Annotated Preference Data across Diverse Tasks and Languages—0
Holistic Capability Preservation: Towards Compact Yet Comprehensive Reasoning Models—0
Hi Robot: Open-Ended Instruction Following with Hierarchical Vision-Language-Action Models—0
Hindsight Planner: A Closed-Loop Few-Shot Planner for Embodied Instruction Following—0
Procedures as Programs: Hierarchical Control of Situated Agents through Natural Language—0
Active Reasoning in an Open-World Environment—0
HERM: Benchmarking and Enhancing Multimodal LLMs for Human-Centric Understanding—0
HELPER-X: A Unified Instructable Embodied Agent to Tackle Four Interactive Vision-Language Domains with Memory-Augmented Language Models—0
SteP: Stacked LLM Policies for Web Actions—0
HAPFI: History-Aware Planning based on Fused Information—0
CROME: Cross-Modal Adapters for Efficient Multimodal LLM—0
Aligning Text, Images, and 3D Structure Token-by-Token—0
Mitigating Biases for Instruction-following Language Models via Bias Neurons Elimination—0
Guided Adaptive Credit Assignment for Sample Efficient Policy Optimization—0
Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels—0
Creating Arabic LLM Prompts at Scale—0
Ground-level Viewpoint Vision-and-Language Navigation in Continuous Environments—0
Language Conditioned Imitation Learning over Unstructured Data—0
AutoRT: Embodied Foundation Models for Large Scale Orchestration of Robotic Agents—0
Grounding Language by Continuous Observation of Instruction Following—0
CoTBal: Comprehensive Task Balancing for Multi-Task Visual Instruction Tuning—0
GROOT: Learning to Follow Instructions by Watching Gameplay Videos—0
GROOT-2: Weakly Supervised Multi-Modal Instruction Following Agents—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