HuggingFace
Motif 3: Technical Report
We introduce Motif 3, a decoder-only Mixture-of-Experts language model with 314 billion total parameters and 13.2 bil...
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HuggingFace
SWE-Bench ProMax: Benchmarking Agents on Large-Scale Multilingual Code Refactoring
As AI coding agents take on increasingly complex, long-horizon software engineering tasks, existing benchmarks are ra...
HuggingFace
Macaron-V1: Towards Open Continual Learning with Self-Improvement and Mixture-of-LoRA
Macaron-V1 is an open agent-model family for experiential intelligence: learning from experience in real environments...
HuggingFace
Intent Speaks Louder: Controllable User Simulation Beyond Response Imitation
User simulators are widely used as scalable environments for training and evaluating interactive assistants. Generati...
HuggingFace
Evo-Bench: Can Language Models Improve Agent Harness?
Large Language Models (LLMs) have driven rapid progress in autonomous agents, yet standard evaluations remain confine...
HuggingFace
Ouroboros: A Self-Developing Frontier Coding Agent with Reviewed Core Evolution
We present Ouroboros, a self-developing agent harness whose tools, prompts, context assembly, and core implementation...
HuggingFace
Factorized Hypothesis Search for Evidence-to-Taxonomy Retrieval
Large-taxonomy retrieval often assumes that the input already expresses the target concept. In many settings, however...
HuggingFace
RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance
General-purpose reward models are increasingly the bottleneck for scaling robot learning, yet the recipe for learning...
HuggingFace
Agent Memory Distillation: Empowering Small LLM Agents with Hierarchical Teacher Memory
Memory systems have shown promise for improving agent performance, but their potential remains largely unexplored for...
HuggingFace
OasisKV: Scaling In-Decode KV Cache Beyond HBM with Lookahead Sparse Prefetching
Large language model (LLM) inference serving is increasingly constrained by memory rather than compute. As long-conte...
HuggingFace
Scaling Inherently Interpretable Language Models
Interpretability is often treated as a tax on capability: language models are trained as opaque systems, then explain...
HuggingFace
What to Edit Next: Visually Aligned Image-Editing Follow-Up Suggestions in Conversational Systems
Conversational assistants increasingly recommend follow-up edits to help users continue a task. Existing systems prim...