Knowledge catalogue
arXiv:2609.03729v1 Announce Type: new Abstract: Despite the remarkable prowess of Vision-Language Models (VLMs) in general multimodal tasks, they remain fundamentally ``flat'' when reasoning about the
arXiv:2609.04010v1 Announce Type: new Abstract: Large Language Models (LLMs) owe much of their success to next-token prediction (NTP), but their autoregressive (AR) structure requires slow, sequential
arXiv:2510.20721v4 Announce Type: replace-cross Abstract: Large language models (LLMs) are rapidly being adopted for tasks like drafting emails, summarizing meetings, and answering health questions. I
Overview llama.cpp 0.4.0 adds initial Qwen3.8-Flash-Next and Nemotron-3-Puzzle support, on-demand tensor reading, per-slot server context limits, video input options, and a ggml update to 0.23.0 with
arXiv:2609.02998v1 Announce Type: cross Abstract: On-policy distillation (OPD) accelerates post-training by providing dense token-level supervision from a frozen teacher on the student's own rollouts.
arXiv:2609.03515v1 Announce Type: new Abstract: Decoding-time KV cache compression research focuses heavily on designing better token scoring functions, while the temporal rule that aggregates scores
arXiv:2609.03378v1 Announce Type: new Abstract: Depth can resolve appearance ambiguity in RGB-D salient object detection (SOD), yet sensor depth is not uniformly reliable. Missing regions, blurred bou
arXiv:2609.03554v1 Announce Type: cross Abstract: Generative retrieval has demonstrated significant success by unifying representation learning and search into a single sequence-to-sequence generation
arXiv:2609.02110v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) commonly evaluate the spatial derivatives appearing in partial differential equation residuals using automatic
arXiv:2609.02143v1 Announce Type: cross Abstract: Most vector databases rely on graph-based indexes, notably HNSW and Vamana, for approximate nearest neighbor search. With embedding models widely adop
arXiv:2609.01756v1 Announce Type: new Abstract: Diffusion models have recently emerged as expressive generative priors for planning and control. This paper studies Action Diffusion, an action-sequence
arXiv:2406.16893v3 Announce Type: replace-cross Abstract: The emergence of Transformer-based Large Language Models (LLMs) has substantially augmented the capabilities of Natural Language Processing (N
arXiv:2607.11581v2 Announce Type: replace Abstract: This paper introduces Actor as Its Own Critic, a unified reinforcement learning framework, Cycle Group Relative Policy Optimization (CycleGRPO), tha
arXiv:2609.02821v1 Announce Type: new Abstract: Researchers increasingly use artificial intelligence to construct measures of social, organizational, and occupational characteristics that are absent f
arXiv:2609.01778v1 Announce Type: new Abstract: Large-scale video retrieval requires embedding models to encode long and diverse videos under tight visual-input and inference budgets. Existing methods
arXiv:2609.01757v1 Announce Type: new Abstract: Vision-Language Pretrained Models (VLPMs) offer a scalable path to open-vocabulary chest radiology understanding, yet two aspects remain underexplored:
OpenAI announced that its latest model, **Astra**, is their most aligned AI to date, reporting sizable gains in the ability to understand user intent. The tweet was posted on September 3, 2026 at 7:32
arXiv:2609.02798v1 Announce Type: new Abstract: Neural map matchers estimate an image's 3-DoF pose relative to a 2D map. These models are trained on large-scale datasets of geo-referenced images, whos
arXiv:2609.01861v1 Announce Type: new Abstract: The performance of an LLM agent depends on the scaffold around a frozen model. A common way to improve that scaffold is to use a coding agent as an opti
arXiv:2605.25784v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) have advanced rapidly in remote-sensing analysis, yet existing evaluations remain predominantly 2D-centric.
arXiv:2609.01659v1 Announce Type: cross Abstract: Chain-of-thought (CoT) reasoning powers generative models by eliciting intermediate steps before producing an answer. In autonomous driving, the answe
arXiv:2609.02172v1 Announce Type: new Abstract: Optimization-based jailbreak attacks such as Greedy Coordinate Gradient (GCG) achieve strong effectiveness and transferability by optimizing adversarial
arXiv:2609.02401v1 Announce Type: new Abstract: Autoregressive vision language models unify heterogeneous perception tasks but are highly susceptible to compounding errors. On-policy distillation (OPD
Can a strong general-purpose vision model distinguish real from AI-generated images using only a simple decision rule on frozen representations? Our latest results, to be presented at #ECCV2026, show
arXiv:2609.02265v1 Announce Type: new Abstract: Personalized language agents use persistent memory to adapt to users over time, but the same mechanism creates an attack surface. When new information c
arXiv:2609.01806v1 Announce Type: new Abstract: Shadow removal is an important preprocessing step for many vision tasks, yet existing supervised methods require paired shadow and shadow-free images, w
arXiv:2512.07328v2 Announce Type: replace-cross Abstract: Text-to-video generation has advanced rapidly, yet preserving a character's holistic appearance from a single reference image remains challeng
arXiv:2609.01925v1 Announce Type: cross Abstract: The attention prefilling phase of long-context LLM inference scales quadratically, making self-attention a severe computational bottleneck. Traditiona
arXiv:2609.02028v1 Announce Type: new Abstract: Despite recent advances in large vision-language models (LVLMs), object hallucination remains a major barrier to their reliable deployment. Existing det
arXiv:2609.01609v1 Announce Type: new Abstract: While diffusion models effectively capture multimodal behavioral priors for autonomous driving, offline reinforcement learning (RL) policies remain susc
arXiv:2609.02315v1 Announce Type: cross Abstract: A single sentence often expresses multiple valid relational triplets, which makes Open Information Extraction (OpenIE) fundamentally a multi-output ta
arXiv:2609.02252v1 Announce Type: cross Abstract: In trajectory planning for autonomous driving, hybrid planning architectures are often realized as a collection of disparate modules, each with its ow
arXiv:2609.02885v1 Announce Type: new Abstract: Recent web agents use world models for test-time action selection by sampling candidate actions, predicting the resulting web states, and ranking them w
arXiv:2511.20251v2 Announce Type: replace Abstract: Modern text-to-image models produce impressive visual results from richly specified prompts, yet their behavior under long prompts remains insuffici
arXiv:2506.00290v2 Announce Type: replace Abstract: This paper introduces DLM-One, a score-distillation-based framework for one-step sequence generation with continuous diffusion language models (DLMs
arXiv:2609.02707v1 Announce Type: new Abstract: Does the door-in-the-face technique work on language models? In humans, a large request that is refused makes a smaller follow-up request more likely to
arXiv:2501.18143v2 Announce Type: replace Abstract: Min cut is an important graph partitioning method. However, current solutions to the min cut problem suffer from slow speeds, difficulty in solving,
arXiv:2609.02075v1 Announce Type: new Abstract: Industrial anomaly detection benefits from anomaly samples, yet newly deployed products typically provide only normal images, making anomaly samples dif
arXiv:2603.06662v3 Announce Type: replace Abstract: Continual VideoQA with multimodal LLMs remains challenging because sequential adaptation induces task interference, while storing task-specific prom
arXiv:2609.02068v1 Announce Type: new Abstract: Probabilistic multivariate time series (MTS) forecasting is crucial for modeling complex dynamical systems. However, existing diffusion-based methods re
arXiv:2609.02309v1 Announce Type: new Abstract: GUI agents increasingly operate across websites, mobile apps, and desktop environments, yet the field still reports progress primarily through task succ
arXiv:2606.13081v2 Announce Type: replace-cross Abstract: Emotion significantly influences cognition, enhancing memory and learning under certain conditions. Drawing on this principle, emotion-augment
arXiv:2609.01742v1 Announce Type: new Abstract: Anti-UAV systems increasingly fuse multiple sensors, yet their detection heads provide no per-modality reliability signal. This study evaluates whether
arXiv:2509.06272v5 Announce Type: replace-cross Abstract: Swarm-based optimization algorithms have demonstrated remarkable success in solving complex problems, yet their widespread adoption remains li
arXiv:2609.02101v1 Announce Type: cross Abstract: Federated learning (FL) lets institutions train a shared model without exchanging data, and Low-Rank Adaptation (LoRA) makes this practical at scale b
arXiv:2609.02529v1 Announce Type: cross Abstract: Image enhancement and restoration have become standard back-end operations on short-video and social media platforms to boost UGC visual experience. Y
arXiv:2609.02640v1 Announce Type: new Abstract: The rapid advancement of generative models has significantly worsened the problem of manipulated image detection, as these methods are capable of produc
arXiv:2609.02813v1 Announce Type: new Abstract: Text-to-image models excel at natural image synthesis but struggle with graphic design, where success depends on satisfying precise constraints on typog
arXiv:2609.02162v1 Announce Type: cross Abstract: Serving useful recommendations under distribution shift is crucial for balancing utility and risk in out-of-distribution (OOD) recommendation. However
arXiv:2609.02683v1 Announce Type: new Abstract: Earth observation is fundamentally multi-scale; geospatial tasks span varied resolutions, and satellite imagery is organized into cascading tile pyramid
arXiv:2603.03718v2 Announce Type: replace Abstract: Glass surface segmentation from RGB images is a challenging task, with a number of applications in robotics and scene understanding. As glass lacks
I've been using Deepseek V4 Flash 0731 for a few weeks now and while I havent thrown it anything very hard, im quite happy with it. Using through antirez's great ds4 project. They've added support for
For the ninth consecutive year, Gartner® has named Google a Leader in the Gartner Magic Quadrant™ for Strategic Cloud Platform Services, positioned furthest for Completeness of Vision. We believe this
GPT-6 Astra is state-of-the-art on FrontierMath Tier 4, ARC-AGI 3, and TerminalBench-4.0. GPT‑6 Astra is also a major advance for scientific discovery, with state-of-the-art performance on Terminal-Be
GPT-6 Astra is the most intelligent and aligned model in the world, and sets a new state of the art for computer use, browsing, software engineering, cybersecurity, science, and professional work. htt
arXiv:2312.06315v2 Announce Type: replace Abstract: Warning: This paper contains content that may be offensive or upsetting. There has been a significant increase in the usage of large language models
arXiv:2609.01723v1 Announce Type: cross Abstract: Text-to-Speech (TTS) foundation models are increasingly fine-tuned on private datasets to synthesize highly personalized voices, introducing severe pr
arXiv:2609.02422v1 Announce Type: new Abstract: Broad Learning System is an efficient randomized learning model that expands network width through feature and enhancement nodes and estimates the outpu
I want to share a short paper just published exploring a simple but surprisingly effective optimization for sparse MoE reasoning models. The idea: Instead of retraining anything, we just tweak the rou
arXiv:2609.02004v1 Announce Type: cross Abstract: Accurate segmentation of polyps and skin lesions is pivotal for clinical diagnosis, yet existing methods struggle with low contrast, ambiguous boundar