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1-Bit Bonsai Image 4B Image Generation for Local Devices
Introducing 1-bit and Ternary Bonsai Image 4B: Image Generation for Local Devices Today we’re releasing Bonsai Image 4B, a family of compact image-generation models designed to run high-quality diffusion inference on local hardware: from laptops to phones. Bonsai Image 4B comes in two variants: - 1-bit Bonsai Image 4B uses binary {−1, +1} transformer weights with an FP16 group-wise scaling factor, giving 1.125 effective bits per weight. It targets maximum compression and is the right fit...
Albania Is Not for Sale: Kushner's $4B Resort Triggers'Flamingo Revolution'
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Mellum2 Technical Report
arXiv:2605.31268v1 Announce Type: new Abstract: We present Mellum 2, an open-weight 12B-parameter Mixture-of-Experts (MoE) language model with 2.5B active parameters per token. Mellum 2 is a general-purpose language model specialized in software engineering, spanning code generation and editing, debugging, multi-step reasoning, tool use and function calling, agentic coding, and conversational programming assistance, and it is the successor to the completion-focused 4B dense Mellum model. The...
Wall-OSS-0.5 Technical Report
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Temporal Preference Concepts and their Functions in a Large Language Model
Announce Type: new Abstract: Large Language Models (LLMs) are increasingly being deployed to make decisions that require trading off near-term gains against long-term consequences, yet little is known about how they internally represent or resolve these tradeoffs. In this work, we causally localize an underlying subgraph for temporal preference in a distilled LLM (Qwen3-4B-Instruct-2507), identifying mid-to-upper-layer nodes through converging evidence from gradient-based attribution and...
From "Weak" Signals to Strong Models: Preference Delta Aggregation with LoRA Merging
arXiv:2606.00357v2 Announce Type: replace Abstract: Training strong large language models (LLMs) requires high-quality supervision, which is often scarce. Recent work shows that paired preference data from weak-weaker model pairs (e.g., Qwen3 4B over 1.7B), despite the limited quality of individual responses, can provide an effective supervision signal through relative quality deltas, which we term a "weak" signal. This motivates a key research question: can multiple "weak" signals be...
Diagnosing Failure Modes of Shared-State Collaboration in Resource-Constrained Visual Agents
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How Small Can You Go? LoRA Fine-Tuning 270M-8B Models for Merchant Information Extraction in Financial Transactions
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Molecular glue degraders of HuR suppress BRAF-mutant colorectal cancer
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OpenWebRL: Demystifying Online Multi-turn Reinforcement Learning for Visual Web Agents
Announce Type: replace Abstract: Building capable visual web agents requires long-horizon reasoning, precise grounding, and robust interaction with dynamic real-world websites. Despite rapid progress, the strongest systems remain largely proprietary, while open agents still depend heavily on supervised post-training over large collections of curated web trajectories. This dependence creates a major scalability bottleneck: high-quality demonstrations are expensive to collect, and static...