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Instruction Following
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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.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
DrafterBench: Benchmarking Large Language Models for Tasks Automation in Civil Engineering
How Many Instructions Can LLMs Follow at Once?
Multilingual Multimodal Software Developer for Code Generation
TuneShield: Mitigating Toxicity in Conversational AI while Fine-tuning on Untrusted Data
Meta SecAlign: A Secure Foundation LLM Against Prompt Injection Attacks
DeSTA2.5-Audio: Toward General-Purpose Large Audio Language Model with Self-Generated Cross-Modal Alignment
Kwai Keye-VL Technical Report
LLaVA-Pose: Enhancing Human Pose and Action Understanding via Keypoint-Integrated Instruction Tuning
Bridging Offline and Online Reinforcement Learning for LLMs
Multi-lingual Functional Evaluation for Large Language Models
Learning Instruction-Following Policies through Open-Ended Instruction Relabeling with Large Language Models
JarvisArt: Liberating Human Artistic Creativity via an Intelligent Photo Retouching Agent
InstructTTSEval: Benchmarking Complex Natural-Language Instruction Following in Text-to-Speech Systems
Treasure Hunt: Real-time Targeting of the Long Tail using Training-Time Markers
Mixture of Weight-shared Heterogeneous Group Attention Experts for Dynamic Token-wise KV Optimization
Instruction Following by Boosting Attention of Large Language Models
LeVERB: Humanoid Whole-Body Control with Latent Vision-Language Instruction
CMI-Bench: A Comprehensive Benchmark for Evaluating Music Instruction Following
MM-R5: MultiModal Reasoning-Enhanced ReRanker via Reinforcement Learning for Document Retrieval
HalLoc: Token-level Localization of Hallucinations for Vision Language Models
AC/DC: LLM-based Audio Comprehension via Dialogue Continuation
Discovering Hierarchical Latent Capabilities of Language Models via Causal Representation Learning
Conversational Search: From Fundamentals to Frontiers in the LLM Era
Magistral
Alzheimer's Dementia Detection Using Perplexity from Paired Large Language Models
VerIF: Verification Engineering for Reinforcement Learning in Instruction Following
EIFBENCH: Extremely Complex Instruction Following Benchmark for Large Language Models
RHealthTwin: Towards Responsible and Multimodal Digital Twins for Personalized Well-being
LLaVA-c: Continual Improved Visual Instruction Tuning
LeVo: High-Quality Song Generation with Multi-Preference Alignment
Video Unlearning via Low-Rank Refusal Vector
Aligning Text, Images, and 3D Structure Token-by-Token
Adversarial Paraphrasing: A Universal Attack for Humanizing AI-Generated Text
Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework
Audio-Aware Large Language Models as Judges for Speaking Styles
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