Instruction Following
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Benchmarks
Most implemented
QLoRA: Efficient Finetuning of Quantized LLMs
Self-Instruct: Aligning Language Models with Self-Generated Instructions
Visual Instruction Tuning
Habitat: A Platform for Embodied AI Research
Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks
ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools
Papers
SenseNova-U1.5: Towards Native Unified Visual Intelligence
We launch SenseNova-U1.5, an 8B-MoT native unified multimodal model that understands, reasons about, and generates visual content within an encoder-free and VAE-free architecture. We strengthen its visual interface throu…
Reinforcement LearningInstruction FollowingImage EditingVidu S2: Real-Time Interactive, Editable, and Spatial Video Generation
We present Vidu S2, which comprises Vidu S2-Avatar, a real-time interactive digital-character model, and Vidu S2-Editing, a real-time video editing model. Moreover, we explore the feasibility of real-time spatial video g…
Instruction FollowingVideo GenerationBuilding Multilingual Bridges: Data Mixing as the Pillar of Generalization for In-Language Reasoning
Reasoning language models have made substantial advances on a variety of complex tasks, yet their capabilities remain overwhelmingly English-centric: models primarily reason in English regardless of the language they are…
Instruction FollowingNeoHorse-1: Towards Recursive Self-Improvement via Agentic Post-Training with Routing Harness
Recursive self-improvement (RSI) requires a concrete mechanism through which an AI system observes its capabilities and converts that evidence into the next round of learning. We present NeoHorse-1, a family of agent-nat…
Instruction FollowingMobileVLA-R1 2.0: RL-Enhanced Reasoning for Mobile Robot Control
Grounding natural-language instructions into reliable and executable actions remains a fundamental challenge for vision-language-action (VLA) systems on mobile robots, due to the persistent gap between high-level semanti…
Reinforcement LearningInstruction FollowingMultimodal ReasoningDecision MakingEuroAlpaca: Task-Preserving Localisation of Instruction Data for European Languages
Machine translation (MT) offers a scalable way to extend English instruction-tuning data to multiple languages, but it can distort task-critical constraints and required outputs, creating corrupted training examples and …
Instruction FollowingMachine Translation