[Megathread] Qwen3.8-Flash-Next - Release Day
Megathread for discussing the (impending) release of Qwen 3.8 Flash Next. Quants Fine-Tunes & Abliterations Chat Templates Inference Server Support & Configuration Experiences, Benchmarks & Model Comp
Knowledge catalogue
Megathread for discussing the (impending) release of Qwen 3.8 Flash Next. Quants Fine-Tunes & Abliterations Chat Templates Inference Server Support & Configuration Experiences, Benchmarks & Model Comp
arXiv:2608.23936v1 Announce Type: new Abstract: We present a dynamical-systems based model for resting-state functional magnetic resonance imaging (rs-fMRI), trained on a dataset of roughly 40K rs-fMR
arXiv:2608.23897v1 Announce Type: cross Abstract: When a code generating language model fabricates a Python package name, an adversary who has pre-registered that name on PyPI can convert that halluci
arXiv:2608.24310v1 Announce Type: new Abstract: Search-augmented reasoning remains difficult for small language models. On-policy distillation (OPD) from trained teachers offers a promising direction,
arXiv:2608.24073v1 Announce Type: cross Abstract: Low-earth-orbit (LEO) satellites enable high-resolution, large-scale Earth observation for applications such as disaster monitoring and environmental
arXiv:2608.24115v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) can integrate long visual histories, reason under partial observability, and infer behavior from a few exampl
arXiv:2608.23906v1 Announce Type: new Abstract: Artificial Intelligence (AI) is increasingly integrated into complex sociotechnical systems, including Critical National Infrastructure (CNI), where har
arXiv:2608.24263v1 Announce Type: new Abstract: Change data synthesis provides a cost-effective solution for expanding training data and improving the performance of change detection models. However,
arXiv:2608.24876v1 Announce Type: new Abstract: Recursive self-improvement (RSI) remains hard in long-horizon tasks, where growing histories obscure the task state and misalign skill invocation. We in
arXiv:2608.24135v1 Announce Type: new Abstract: Reinforcement learning from verifiable rewards (RLVR) has emerged as a pivotal technique for enhancing the code generation capabilities of Large Languag
arXiv:2608.24173v1 Announce Type: new Abstract: Quantization correction methods usually optimize weights, quantization parameters, or reconstruction objectives, while the underlying parameter subspace
arXiv:2608.24516v1 Announce Type: cross Abstract: Satellite-based distributed learning promises to train machine-learning models directly in orbit using massive, globally dispersed sensor data, thereb
arXiv:2608.24119v1 Announce Type: cross Abstract: Visual demonstrations provide a natural interface for specifying image transformations that are difficult to describe exhaustively with text. However,
arXiv:2508.21424v3 Announce Type: replace Abstract: Deep learning models have achieved state-of-the-art performance in many computer vision tasks. However, in real-world scenarios, novel classes that
arXiv:2510.19347v2 Announce Type: replace-cross Abstract: Most machine learning models are vulnerable to adversarial examples, which poses security concerns on these models. Adversarial examples are c
arXiv:2608.22444v1 Announce Type: new Abstract: The unit of AI safety evaluation is still the individual model, yet language-model agents are increasingly deployed in interacting populations that read
arXiv:2608.21894v1 Announce Type: new Abstract: Human tactile perception relies on complex multisensory cues. Yet the relationship between tactile signals and perceptual representations remains poorly
arXiv:2508.18646v3 Announce Type: replace Abstract: Despite their rapid advancement, large language models (LLMs) suffer from a critical disconnect between benchmark scores and real-world utility. Cur
arXiv:2608.22557v1 Announce Type: cross Abstract: Existing LLM unlearning methods struggle with robustness: unbounded forget losses degrade model coherence, fixed-weight balancing cannot adapt as reta
arXiv:2608.22808v1 Announce Type: new Abstract: When can an agent failure be caught? An audit is usually limited by the record rather than by the method. CatchBench therefore puts one auditor's questi
arXiv:2608.23205v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) have revolutionized reasoning in LLMs, and the increasing public availability of reasoning traces creates valuable opportu
Compute has always been core to the @VerneRobotics story. Getting there meant negotiating long, expensive contracts with big neoclouds, and projecting compute needs years into the future. Verne wasn't
arXiv:2608.23153v1 Announce Type: new Abstract: In high-stakes healthcare applications, machine learning models are frequently trained on data from one patient population and deployed on another, crea
arXiv:2607.27836v2 Announce Type: replace Abstract: Large language model unlearning is consistently fragile under relearn attacks. On TOFU, fine-tuning on twenty forget examples substantially recovers
arXiv:2608.23065v1 Announce Type: cross Abstract: Cultural understanding in video means more than recognizing what is visible; it requires grasping the symbolic and temporal significance of cultural c
arXiv:2608.22745v1 Announce Type: cross Abstract: Emotion Recognition in Conversation (ERC) requires models to identify subtle emotional cues that are often distributed across distant dialogue turns.
arXiv:2608.23268v1 Announce Type: new Abstract: Frontier multimodal large language models (MLLMs) deliver impressive perception yet still falter on scientific and mathematical reasoning. Parameter-lev
arXiv:2608.22996v1 Announce Type: new Abstract: Vision-Language Models (VLMs) perform well on diverse vision-language tasks, but transformer-based visual encoders split images into fixed-resolution su
arXiv:2608.21539v1 Announce Type: new Abstract: Federated Continual Learning (FCL) is fundamental to real-world distributed learning systems, requiring models to adapt to sequential, non-IID data acro
arXiv:2608.23353v1 Announce Type: new Abstract: Mixed-integer programming (MIP) lies at the core of operations research and industrial optimization. While large language models (LLMs) have recently sh
arXiv:2608.21668v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to simulate students at different mastery levels. These simulations can generate synthetic training d
arXiv:2608.21476v1 Announce Type: cross Abstract: Website redundancy does not have a single fixed meaning. The same repeated element may distract during one task and provide backup during another. We
arXiv:2608.21833v1 Announce Type: new Abstract: Recent large language models (LLMs) can operate as coding agents that build complete games from natural language requests. Game development is especiall
arXiv:2608.21467v1 Announce Type: cross Abstract: Gaussian distributions are used to model uncertainty in signals and states, and Gaussian mixtures are often used when the underlying distribution is m
arXiv:2608.21440v1 Announce Type: cross Abstract: Vision-language-action (VLA) models have advanced end-to-end autonomous driving by leveraging foundation models for semantic reasoning and long-tail g
arXiv:2608.22847v1 Announce Type: new Abstract: Vision-Language Models (VLMs) based GUI agents stand to benefit significantly from online reinforcement learning (RL). However, their training is bottle
arXiv:2608.23356v1 Announce Type: cross Abstract: Accurate watch-time (WT) prediction is an important requirement for short-video recommendations. Yet WT distributions are near-zero-inflated, long-tai
arXiv:2608.21756v1 Announce Type: cross Abstract: Deep-learning efforts have increasingly shifted toward foundation model approaches. In experimental physics, this allows models and learned representa
Hello everyone. I hope is all well with you all. I been around this sub for a few months and been quietly reading and I have seen how many of you are spending $10k on the Mac M5 and I am assuming you
arXiv:2608.23061v1 Announce Type: new Abstract: Background: Automating clinical guideline-based decision-making with large language models (LLMs) remains challenging because of reliability, hallucinat
arXiv:2608.22990v1 Announce Type: new Abstract: Vision-language-action (VLA) models have made general-purpose robot manipulation increasingly plausible by conditioning robot actions on natural-languag
arXiv:2602.06064v2 Announce Type: replace-cross Abstract: Scheduling precedence-constrained tasks under shared renewable resources is critical to modern computing platforms. It is often modeled as the
arXiv:2608.22618v1 Announce Type: new Abstract: Individual patient data (IPD) from clinical trials is the substrate for survival modeling, meta-analysis, and safety research, yet IPD is rarely release
arXiv:2608.22142v1 Announce Type: new Abstract: This paper addresses the issue of self-intersecting trajectories (in phase space) in industrial reduced-order modeling and proposes the Latent-Augmented
arXiv:2608.22370v1 Announce Type: new Abstract: Task-specific LoRA adapters offer a modular way to specialize large language and vision-language models. However, existing adapter composition methods a
Hi, I’m having fun using “huihui_ai/Qwen3.6-abliterated:35b-Claude-4.7” for pen testing. It’s uncensored so it does whatever I want. I’m on M4 Pro 14 core 64GB. Just wondering if there are some models
arXiv:2608.22417v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to support text analysis in qualitative research, yet evidence on their performance in inductive cont
Hey everyone, I'm trying to set up a local LLM on my machine. My goal is to use it with Qwen Code or OpenCode to help me out with small to medium sized tasks, but nothing too big. I tested many differ
arXiv:2509.19005v2 Announce Type: replace-cross Abstract: The Minimum Bisection Problem is a fundamental, computationally hard graph partitioning problem with applications in parallel computing, netwo
arXiv:2608.23234v1 Announce Type: new Abstract: In this technical report, we present a training-free framework for audio-guided video object segmentation, which integrates Multimodal Large Language Mo
arXiv:2608.21678v1 Announce Type: cross Abstract: Current work in modeling symbolic music primarily relies on representations extracted from MIDI-like data. While such formats allow for modeling symbo
arXiv:2412.04806v2 Announce Type: replace-cross Abstract: Adapting Large Language Models (LLMs) trained on discrete text data, to forecast continuous time series signals is challenging. While finetuni
arXiv:2606.13610v2 Announce Type: replace-cross Abstract: Search-augmented LLMs increasingly mediate everyday consumer recommendations by retrieving live web content. This creates a new risk: LLM reco
arXiv:2608.23093v1 Announce Type: cross Abstract: We study parameter recovery in the Caldeira--Leggett (quantum Brownian) oscillator from partial moment traces. Our model is a moment-level PINN that p
arXiv:2608.21885v1 Announce Type: new Abstract: Pixel-space diffusion models directly model image distributions but remain difficult to optimize. Recent methods alleviate this challenge through target
arXiv:2412.07264v2 Announce Type: replace-cross Abstract: Understanding complex animal behaviors hinges on deciphering the neural activity patterns within brain circuits, making the ability to forecas
arXiv:2608.22237v1 Announce Type: new Abstract: Long-horizon agents increasingly rely on repeated access to external artifacts, yet current reading interfaces often expose entire objects even when onl
arXiv:2608.22856v1 Announce Type: cross Abstract: A retrieval-augmented QA system can return different answers after an index expansion even when its requested model identifier, prompt, retrieval poli
arXiv:2608.22321v1 Announce Type: new Abstract: Multimodal time-series forecasting has emerged as a promising paradigm in which natural-language context is expected to improve predictive performance.
arXiv:2608.21551v1 Announce Type: cross Abstract: Complex-valued arrays arise in signal processing, where scientific interpretation depends on retaining amplitude and phase information. Existing covar