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 576–600 of 1135 papers

TitleStatusHype
Implicit Cross-Lingual Rewarding for Efficient Multilingual Preference AlignmentCode0
Unified Mind Model: Reimagining Autonomous Agents in the LLM Era—0
CodeIF-Bench: Evaluating Instruction-Following Capabilities of Large Language Models in Interactive Code Generation—0
Robust Learning of Diverse Code Edits—0
LEWIS (LayEr WIse Sparsity) -- A Training Free Guided Model Merging Approach—0
InSerter: Speech Instruction Following with Unsupervised Interleaved Pre-training—0
Iterative Value Function Optimization for Guided Decoding—0
In-context Learning vs. Instruction Tuning: The Case of Small and Multilingual Language Models—0
Re-Imagining Multimodal Instruction Tuning: A Representation ViewCode0
Triple Phase Transitions: Understanding the Learning Dynamics of Large Language Models from a Neuroscience Perspective—0
Layer-Aware Task Arithmetic: Disentangling Task-Specific and Instruction-Following Knowledge—0
DataMan: Data Manager for Pre-training Large Language Models—0
Stay Focused: Problem Drift in Multi-Agent DebateCode0
Hi Robot: Open-Ended Instruction Following with Hierarchical Vision-Language-Action Models—0
Ground-level Viewpoint Vision-and-Language Navigation in Continuous Environments—0
URO-Bench: A Comprehensive Benchmark for End-to-End Spoken Dialogue Models—0
TextGames: Learning to Self-Play Text-Based Puzzle Games via Language Model ReasoningCode0
UrduLLaMA 1.0: Dataset Curation, Preprocessing, and Evaluation in Low-Resource Settings—0
Capability Instruction Tuning: A New Paradigm for Dynamic LLM RoutingCode0
ATEB: Evaluating and Improving Advanced NLP Tasks for Text Embedding Models—0
Order Matters: Investigate the Position Bias in Multi-constraint Instruction FollowingCode0
NatSGLD: A Dataset with Speech, Gesture, Logic, and Demonstration for Robot Learning in Natural Human-Robot InteractionCode0
Sequence-level Large Language Model Training with Contrastive Preference Optimization—0
SOTOPIA-Ω: Dynamic Strategy Injection Learning and Social Instruction Following Evaluation for Social AgentsCode0
OpenSearch-SQL: Enhancing Text-to-SQL with Dynamic Few-shot and Consistency Alignment—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