Qwen3.5 35B A3B
PulseAugur coverage of Qwen3.5 35B A3B — every cluster mentioning Qwen3.5 35B A3B across labs, papers, and developer communities, ranked by signal.
- 2026-08-20 research_milestone The Qwen3.5 35B A3B model achieved a high score on the GPQA benchmark and demonstrated strong cost-efficiency. source
9 day(s) with sentiment data
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New research reveals LLMs learn false claims when trained on negations
A new research paper introduces "Negation Neglect," a phenomenon where large language models, when trained on documents that explicitly state a claim is false, paradoxically learn to believe the claim is true. This effe…
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New WISE framework diagnoses and attributes AI search quality issues
Researchers have introduced WISE, an agentic framework designed to diagnose and attribute poor quality in algorithm-driven services, particularly focusing on industrial search. This framework aims to identify user-facin…
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New LBS model trains vision-language models for active visual observation
Researchers have developed a new method called LBS (Look Beyond Screens) that trains vision-language models to perform active, task-oriented visual observation. This approach uses GUI grounding trajectories as a source …
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WebUniverse system generates verified training data for AI web development agents
Researchers have developed WebUniverse, a system designed to generate verified training data for AI agents focused on web development. This pipeline constructs tasks from open-source repositories and real web pages, cre…
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MMVistaReason enhances multimodal reasoning with new post-training techniques
Researchers have introduced MMVistaReason (MVR), a novel post-training methodology designed to enhance open multimodal reasoning capabilities. MVR addresses challenges in data quality, supervision efficiency, and diffic…
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New benchmark CUA-Recovery highlights agent error-handling weaknesses
Researchers have introduced CUA-Recovery, a new benchmark designed to evaluate the error detection and recovery capabilities of long-horizon computer-use agents (CUAs). Existing benchmarks often overlook these critical …
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Self-HPO framework recursively improves coding agents by optimizing policy and harness
Researchers have introduced Self-HPO, a novel framework designed to recursively improve coding agents by alternating between optimizing the agent's policy and its interaction harness. This approach allows the agent to i…
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ECG-RSI framework boosts Qwen3.5-35B-A3B model accuracy via self-improvement
Researchers have developed ECG-RSI, a novel framework for recursively improving electrocardiogram (ECG) models. This system combines verified waveform synthesis with a feedback-guided search to identify and address mode…
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New 'Handoff Curves' method optimizes multi-turn LLM routing
Researchers have developed a new method called "Handoff Curves" to analyze and optimize multi-turn routing in Large Language Models (LLMs). This approach evaluates how initial model selection, subsequent handoffs, and t…
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LLMs tackle knowledge conflicts, diverse perspectives, and low-resource languages · 7 sources tracked
Recent research explores how large language models handle conflicting information and diverse perspectives. One paper introduces a method for resolving disagreements between a model's internal knowledge and retrieved co…
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DisaggKD enables efficient knowledge distillation by separating teacher and student models
Researchers have developed DisaggKD, a novel knowledge distillation technique that separates teacher and student models across different computing nodes. This approach overcomes memory limitations inherent in traditiona…
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AutoTrust AI releases JEV-35B model with improved performance and NVFP4 version
AutoTrust AI has released autotrust/JEV-35B, a 35 billion parameter open-weights model built on Qwen3.5-35B-A3B. This model demonstrates strong performance across various benchmarks, including significant gains in areas…
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FRIDA Decisions: Open-source Russian-language rapid thinking model released
FRIDA Decisions is an open-source rapid thinking model designed for the Russian language. It can select options, assign scores, answer yes/no, and rank candidates within a single encoder pass, achieving results in milli…
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AI coding agents advance with new optimization, cost control, and safety research
Multiple research papers explore advancements in AI coding agents, focusing on improving their efficiency, reliability, and safety. Self-HPO introduces a recursive framework to optimize both the agent's policy and its i…
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AI learns to forecast events by searching and gathering evidence
Researchers have developed a novel approach to training AI models for event forecasting by integrating a learning-to-search mechanism. This method allows the AI agent to actively gather evidence through web searches and…
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Open-weight LLMs see dramatic price drops, some by over 70% · 8 sources tracked
Several open-weight large language models have seen significant price reductions in their output token costs over the past 30 days. Models like Qwen3.5-35B-A3B, Kimi K2.6, DeepSeek V4 Pro 0423, and Qwen3 VL 30B A3B Thin…
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AutoGUIWorld framework synthesizes GUI interaction data for AI agents
Researchers have developed AutoGUIWorld, a novel framework that synthesizes GUI interaction trajectories for training AI agents. This system leverages image generators and planners to create realistic interaction data w…
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MetaRSI-v1 advances AI self-improvement capabilities · 1 source tracked
CosmosMind, in collaboration with several universities, has introduced MetaRSI-v1, a novel meta-recursive architecture designed to improve the process of recursive self-improvement (RSI) in AI models. This new framework…
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Open-weight AI models advance with new architectures and agent capabilities · 1 source tracked
This week's AI developments highlight advancements in open-weight models, with Qwen and Z.ai introducing new sparse/hybrid architectures focused on inference cost and quality. Apodex released a practical 36B/3B-active M…
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Qwen3.5 35B A3B model achieves high GPQA score and cost-efficiency
The Qwen3.5 35B A3B model has demonstrated impressive performance, achieving an 81.9% score on the GPQA benchmark. It also offers a high intelligence-to-cost ratio, delivering 35.3 intelligence points per dollar. The mo…