Knowledge catalogue
Given the commentary on the Q3.8FN release page here https://qwen.ai/blog?id=qwen3.8-flash-next I assume/hope that all the work that's going on to optimise the hell out of running it will be useful wh
Auto-generated synthesis of 21430 entries about arxiv-cs-lg
Not a bot. Not a Strata shill. Just sharing my experience. So, I have an R9700 in my machine, plus an RTX 5060 Ti, and 64GB DDR5 system RAM. Overall, not a bad setup. Anyway, I mainly run a daily driv
I have been running the same midrange card for a couple of years now, and every model release sends me back to the price sheets. The performance gains are real but they keep landing next to price tags
Clef Flash (9 billion‑parameter) is a multimodal model hosted on Ollama that converts a given state and a schema of typed questions into actionable decisions. Its counterpart, Clef, is also available
I just made the most expressive real-time motion harness for the Reachy Mini. It was created by: > synthesizing a massive motion dataset using Astra (over 10000 samples) > fine-tuning Qwen 3.5 4B usin
Full disclaimer: I've leaned heavily on Fable to develop this, but I've tested it thoroughly on my own library for a couple of months before putting it on GitHub. I live in Thailand, and it started as
.@OpenRouter co-founder Alex Atallah, in his first podcast since Stripe acquired the company, joins @Replit co-founder Amjad Masad and a16z's Erik Torenberg on why the future of AI is independence and
Reasoning from scratch, round number 6! An introduction (and implementation) of Reinforcement Learning with Verifiable Rewards (RLVR) and Group Relative Policy Optimization (GRPO). 00:00 Introduction
arXiv:2610.02116v1 Announce Type: new Abstract: A comparative explainability framework is presented to audit DeBERTa-v3 under zero-shot classification of medical abstracts. The work addresses the disa
Editor’s note: AI21 Labs is a leading global AI lab with a long track record of building foundation models, most notably the Jamba family, and today focuses on specialized LLMs and agent optimization
arXiv:2610.00706v1 Announce Type: cross Abstract: Large audio-language models (LALMs) are sensitive to input perturbations, such as noise, waveform corruption, and adversarial injections. We propose A
arXiv:2610.00988v1 Announce Type: new Abstract: Cryptic ligand-binding pockets are not apparent in experimentally determined apo structures, making them difficult to identify from unbound receptor geo
arXiv:2610.00663v1 Announce Type: new Abstract: Backdoored large language models (LLMs) can behave normally on benign inputs while producing attacker-specified outputs under hidden triggers. Existing
arXiv:2610.01415v1 Announce Type: new Abstract: Large language model (LLM) agents can now undertake increasingly complex tasks, but the way they organize interaction history into memory does not ensur
arXiv:2610.01116v1 Announce Type: new Abstract: As the capabilities and ubiquity of Large Language Models (LLMs) grow, so does their environmental footprint. Despite calls for responsible AI, the mach
arXiv:2602.02269v2 Announce Type: replace-cross Abstract: We present multipanda_ros2, a novel open-source ROS2 architecture for multi-robot control of Franka Robotics robots. Leveraging ros2 control,
arXiv:2610.00894v1 Announce Type: new Abstract: Recent works on continuous diffusion for discrete data have demonstrated performance on par with comparable discrete diffusion models. However, these co
arXiv:2610.00673v1 Announce Type: cross Abstract: Looped language models increase effective depth by repeatedly applying a shared block of layers, but existing large-scale recipes require multi-stage
arXiv:2610.01258v1 Announce Type: new Abstract: Autonomous colonoscopic navigation can reduce operator burden and the risk of loop formation or tissue trauma, but remains challenging due to deformable
arXiv:2610.00418v1 Announce Type: new Abstract: Scaling Transformers to long contexts is constrained by the quadratic cost of self-attention and the linear growth of key-value cache memory transfer. S
arXiv:2610.00973v1 Announce Type: new Abstract: Science teachers frequently search for documentary excerpts not by describing what appears on screen, but by querying the abstract concepts they intend
arXiv:2610.02185v1 Announce Type: new Abstract: Looped Transformers achieve parameter efficiency by repeatedly executing a shared block across recurrent loops. Each loop yields an intermediate represe
arXiv:2610.01355v1 Announce Type: cross Abstract: We introduce a new framework for one-step generative modelling on finite state spaces. To extend drifting beyond continuous domains, we use discrete W
arXiv:2610.01955v1 Announce Type: new Abstract: Outcome-based reinforcement learning can train language models to forecast real-world events, but prior forecasting work either freezes research context
arXiv:2610.00040v1 Announce Type: new Abstract: Recent advances in 3D Gaussian Splatting have enabled open-vocabulary and referring segmentation by distilling semantic knowledge from 2D foundation mod
arXiv:2606.19483v2 Announce Type: replace Abstract: Vision Foundation Models (VFMs) with Vision Transformer (ViT) backbones, such as DINOv2, have become essential for downstream tasks like object reco
arXiv:2610.01210v1 Announce Type: new Abstract: Egocentric video has become a primary source of supervision for embodied models, and its value rests on recovering hand motion in world coordinates, whi
arXiv:2610.00136v1 Announce Type: cross Abstract: This paper presents a reproducible, educational study of evasion attacks in image classification and text classification. A compact convolutional netw
arXiv:2610.01619v1 Announce Type: cross Abstract: The environmental impact of deep learning has attracted increasing attention over the past decade. Existing studies mainly focus on the energy and car
arXiv:2610.02144v1 Announce Type: new Abstract: We introduce Faynt, a family of 10M- and 75M-parameter Transformer policies for Super Smash Bros. Melee, each controlling all 26 characters with a singl
arXiv:2610.01638v1 Announce Type: new Abstract: Federated learning (FL) on heterogeneous edge devices must jointly accommodate unequal resource budgets and domain-shifted local data. Existing resource
arXiv:2610.00858v1 Announce Type: new Abstract: Background and Objective: Clinicians expect recurrence risk to climb with cancer severity. In a UK multicentre trial, an unconstrained XGBoost model lea
arXiv:2610.00009v1 Announce Type: new Abstract: Frequency-collapse attention [Zeris, 2026e] achieves large gains over standard dot-product attention by replacing the Q/K dot product with a bandpass-fi
arXiv:2610.00515v1 Announce Type: cross Abstract: Neural operators learn maps between function spaces, while hereditary network dynamics are described by Volterra resolvents with non-rational Laplace
arXiv:2610.00580v1 Announce Type: new Abstract: In collaborative foundation model fine-tuning, client data is rarely homogeneous. Instead, clients typically possess unknown mixtures of distinct data d
arXiv:2610.00447v1 Announce Type: new Abstract: Can a text-to-3D leaderboard change when every generated scene stays fixed? We audit this question for rendered-image evaluation, where camera settings
arXiv:2511.21507v2 Announce Type: replace Abstract: The effectiveness of deepfake detection methods often depends less on their core design and more on implementation details such as data preprocessin
arXiv:2604.01997v2 Announce Type: replace Abstract: Gait analysis provides an objective characterization of locomotor function and is widely used to support diagnosis and rehabilitation monitoring acr
arXiv:2610.00196v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have shown strong potential for video understanding and caption generation, but their performance may decline i
**DISCLAIMER** THE PREFILLING TPS SHOWN ON THE PHONE IS COMPUTED ONLY FOR THE LAYERS IT HOLDS. ALREADY FIXING IT TO SHOW END-TO-END PREFILL RATE. NUMBERS BELOW ARE ACCURATE FOR E2E PREFILL RATE. Every
arXiv:2610.00355v1 Announce Type: new Abstract: Efficient indoor LiDAR perception is challenging because mobile robots must understand cluttered three-dimensional environments under strict latency and
arXiv:2610.01288v1 Announce Type: new Abstract: Dynamic Movement Primitives (DMPs) provide a compact and stable formulation for trajectory representation and generalization in robot skill learning. Ho
arXiv:2610.01269v1 Announce Type: new Abstract: Bayesian Optimisation (BO) is a powerful framework for the optimisation of expensive black-box functions, but typically requires refitting a surrogate a
arXiv:2610.01351v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have achieved high task success rates on robot manipulation task benchmarks. More recently, there has been an emphas
arXiv:2510.15125v3 Announce Type: replace-cross Abstract: Social media platforms play a pivotal role in shaping political discourse, but the scale and rapid evolution of online content make systematic
arXiv:2610.01079v1 Announce Type: cross Abstract: Machine-learning Network Intrusion Detection Systems (IDS) depend on substantial labeled datasets and task-specific training, whereas Large Language M
arXiv:2610.00855v1 Announce Type: new Abstract: Accurate 3D semantic perception is critical for safe autonomous navigation. However, supervised LiDAR segmentation remains tied to closed taxonomies and
arXiv:2610.01502v1 Announce Type: new Abstract: Diffusion models are a powerful generative paradigm used across multimedia and scientific applications. Guided diffusion methods impose requirements on
arXiv:2610.01668v1 Announce Type: new Abstract: Bio-inspired tendon-driven rigid-soft coupled dexterous fingers exhibit strong nonlinearity and configuration-dependent sensitivity, making accurate mod
arXiv:2610.01236v1 Announce Type: new Abstract: Collaboration between a small language model (SLM) and a large language model (LLM) offers an opportunity to combine the efficiency of smaller models wi
arXiv:2610.00609v1 Announce Type: new Abstract: Legal research is a core and time-consuming legal workflow. Lawyers must identify controlling authority, verify that it remains valid, reconcile statute
arXiv:2610.00318v1 Announce Type: cross Abstract: Simplified optical systems often exhibit residual lens aberrations and Veiling Glare (VG), resulting in spatially varying blur and contrast reduction.
arXiv:2610.01409v1 Announce Type: new Abstract: Reliable uncertainty estimation is essential for deploying object detectors when distribution/covariate shift and adversarial attacks may occur. Existin
arXiv:2601.07148v4 Announce Type: replace-cross Abstract: Tool use, such as web search, has become a standard capability even in freely available large language models (LLMs). However, existing benchm
arXiv:2610.01685v1 Announce Type: new Abstract: Constructive neural combinatorial optimization (NCO) has emerged as a promising paradigm that learns to construct solutions to combinatorial optimizatio
arXiv:2610.02136v1 Announce Type: cross Abstract: Unsupervised anomaly detection (UAD) methods for brain MRI are ranked by a single score, yet that score rests on choices that are rarely reported: how
arXiv:2610.00367v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models enable parameter scaling with limited per-token computation by activating only a small subset of experts for each token,
arXiv:2610.02153v1 Announce Type: new Abstract: Long-horizon autoregressive video generation is limited by a finite context window. When an object or scene falls out of context, its fine-grained visua
arXiv:2610.00148v1 Announce Type: cross Abstract: Open-ended artificial life systems must acquire diverse competencies from a single evolving genotype. Biological brains combine neuromodulation, which