Knowledge catalogue
arXiv:2508.15851v2 Announce Type: replace Abstract: Despite rapid progress in large language models (LLMs), current QA benchmarks still overlook the core challenge of real-world scientific information
arXiv:2606.05569v1 Announce Type: new Abstract: Mispronunciation Detection and Diagnosis (MDD) has gained increasing importance in computer-assisted language learning and speech technology in recent y
arXiv:2606.05233v1 Announce Type: cross Abstract: Recent computer-using-agent (CUA) red-teaming papers report prompt-injection attack success rates (ASR) of 42-98%, but these headline numbers cluster
arXiv:2601.21288v2 Announce Type: replace-cross Abstract: Autonomous driving is an important and safety-critical task, and recent advances in LLMs/VLMs have opened new possibilities for reasoning and
arXiv:2606.05179v1 Announce Type: new Abstract: Punctuation restoration improves ASR (Automatic Speech Recognition) readability. However streaming ASR requires online decisions with limited future con
arXiv:2605.24500v2 Announce Type: replace Abstract: This technical report presents our solution, EgoAdapt (Egocentric Adaptation via Category, Calibration, and Consistency), to the CVPR 2026 HD-EPIC V
arXiv:2606.06038v1 Announce Type: new Abstract: We study English-to-Prakrit machine translation in a low-resource setting where the target language is unsupported by IndicTrans2. We adapt the multilin
arXiv:2606.05168v1 Announce Type: new Abstract: Training on synthetic data causes model collapse, but existing analyses treat this as single-chain degradation. In reality, the AI ecosystem involves cr
arXiv:2606.05874v1 Announce Type: new Abstract: Current evaluations for Multimodal Large Language Models (MLLMs) overwhelmingly focus on utility-driven objectives, leaving model behavior under logic-n
even though @activegraphai is not a memory tool, it's a runtime built around memory so it can do well there cool to see a third party verify this and see that activegraph does well on privacy programs
arXiv:2511.10254v2 Announce Type: replace Abstract: Facial Emotion Analysis (FEA) extends traditional facial emotion recognition by incorporating explainable, fine-grained reasoning. The task integrat
arXiv:2606.05949v1 Announce Type: new Abstract: Scientific illustrations are essential tools for communicating research findings, especially in natural science, where they visualize complex concepts a
arXiv:2408.11336v3 Announce Type: replace-cross Abstract: Climate change stands as one of the most pressing global challenges of the twenty-first century, with far-reaching consequences such as rising
arXiv:2606.06211v1 Announce Type: new Abstract: Automatic speech recognition (ASR) has advanced remarkably for standard speech; however, pathological speech from neurological conditions remains a sign
arXiv:2606.06266v1 Announce Type: new Abstract: Hate speech detection is inherently subjective: people from different demographic groups perceive the same content very differently. Collecting enough a
arXiv:2602.19190v4 Announce Type: replace Abstract: Research on the intelligent interpretation of all-weather, all-time Synthetic Aperture Radar (SAR) is crucial for advancing remote sensing applicati
Gemma 4 QAT is here. Available for all sizes of Gemma 4, optimized with Quantization-Aware Training (QAT) to reduce memory requirements while preserving performance. Live now in LM Studio. https://lms
Gemma 4 Quantization-Aware Training (QAT) weights are now available on Ollama! They reduce memory requirements while maintaining model quality. E2B: ollama run gemma4:e2b-it-qat E4B: ollama run gemma4
arXiv:2606.05175v1 Announce Type: new Abstract: We study generic triple-latent sequence models that maintain a running token state and compressed pair-memory pathway to capture higher-order token inte
arXiv:2603.08491v2 Announce Type: replace Abstract: Cross-modal Geo-localization (CMGL) matches ground-level text descriptions with geo-tagged aerial imagery, which is crucial for pedestrian navigatio
Kate Conger / New York Times: Google Cloud says its SpaceX compute deal is a “short-term” agreement “to ensure we have bridge capacity to meet surging customer demand” for Gemini Enterprise — Elon Mus
arXiv:2511.20158v2 Announce Type: replace Abstract: While continual visual instruction tuning (CVIT) has shown promise in adapting multimodal large language models (MLLMs), existing studies predominan
arXiv:2606.06109v1 Announce Type: new Abstract: Entity alignment (EA) aims to identify equivalent entities across heterogeneous knowledge graphs (KGs) and is a key component of knowledge fusion and cr
Here’s this week’s shipping recap 👇 — Nano Banana 2 & Nano Banana Pro are now GA and available via the Gemini Enterprise Agent Platform, Gemini API, and in @GoogleAIStudio —Co-Scientist, our new multi
arXiv:2601.02730v3 Announce Type: replace Abstract: Visual localization on standard-definition (SD) maps has emerged as a promising low-cost and scalable solution for autonomous driving. However, exis
arXiv:2606.06388v1 Announce Type: cross Abstract: Recent advances in LLM agents have enabled complex cognitive capabilities, such as multi-step reasoning, planning, and tool use, that increasingly pos
I always appreciate the opportunity to discuss @LawZero_ and our approach to honest, reliable AI. Working on the Scientist AI with my brilliant colleagues at LawZero has made me very confident that we
arXiv:2606.06044v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has shown strong effectiveness in grounding Large Language Models (LLMs) with external knowledge. However, existing
This post appears to reference Claude AI's capabilities and performance, likely highlighting how the model has been used or endorsed by notable researchers or Nobel Prize winners to establish credibil
arXiv:2606.06197v1 Announce Type: new Abstract: Question answering (QA) systems have achieved notable progress with the advent of large language models (LLMs). However, they still face challenges in a
arXiv:2606.05172v1 Announce Type: cross Abstract: Diffusion-based image editing has achieved strong visual fidelity under natural language instructions, yet most existing systems still operate at the
arXiv:2606.05624v1 Announce Type: new Abstract: Text-conditioned 3D human motion models now synthesize plausible motions from prompts, but practical animation and embodied-agent workflows rarely stop
arXiv:2606.06087v1 Announce Type: new Abstract: Agent systems increasingly use textual skills to encode reusable task procedures, but injecting these skills into the prompt at every step incurs substa
arXiv:2606.05538v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models achieve strong performance through conditional computation, but their large parameter footprint poses deployment chall
arXiv:2606.05774v1 Announce Type: new Abstract: Dense 3D reconstruction has demonstrated immense potential for spatial understanding, yet its viability as a real-time, onboard representation for auton
arXiv:2606.05354v1 Announce Type: new Abstract: Retinal blood vessel segmentation plays a vital role in the early detection of diabetic retinopathy and glaucoma. While recent deep learning models have
arXiv:2606.05489v1 Announce Type: new Abstract: Retrieval systems underpin modern AI applications -- spanning visual search, recommendation engines, and multi-modal question answering. Modern multi-st
arXiv:2606.05486v1 Announce Type: new Abstract: Prompt ambiguity is a common source of failure in large language models, but is difficult to localize because it is a latent property of the prompt, whi
arXiv:2606.05677v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have advanced image and video understanding and can increasingly handle longer visual inputs. Long-horizon ta
arXiv:2606.06042v1 Announce Type: new Abstract: Developing unified video generation and editing models capable of interpreting interleaved multimodal inputs is a promising yet challenging frontier fie
arXiv:2606.05315v1 Announce Type: new Abstract: Implicit chain-of-thought (iCoT) methods aim to internalize reasoning in large language models, but often underperform explicit CoT prompting. We empiri
arXiv:2603.07294v2 Announce Type: replace Abstract: Fine-grained understanding and species-specific multimodal question answering are vital for advancing biodiversity conservation and ecological monit
arXiv:2606.05177v1 Announce Type: new Abstract: Existing multimodal safety benchmarks focus solely on visual inputs and cannot assess Omni Large Language Models (LLMs) that process vision, audio, and
arXiv:2606.06058v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards is ideal for multi-constraint instruction following, yet standard group-relative policy optimization (G
Nvidia's Nemotron 3 Ultra, an open-source model designed for long-context tasks, is now available to Pro and Max subscribers on Perplexity and Computer. This new model represents Nvidia's latest contr
arXiv:2606.05535v1 Announce Type: new Abstract: Medical visual question answering (Med-VQA) has strong potential for clinical decision support by enabling AI models to interpret medical images and ans
arXiv:2606.05255v1 Announce Type: cross Abstract: Oklab and its cylindrical representation Oklch are widely adopted in interpolation and design workflows as perceptually motivated color spaces, but th
arXiv:2606.05234v1 Announce Type: new Abstract: Wearable exoskeleton systems hold promise for restoring mobility in individuals with physical impairments, yet most existing controllers rely on static
arXiv:2606.06481v1 Announce Type: new Abstract: As AI writing assistants become increasingly integrated into real-world drafting and revision workflows, many documents are no longer purely human-writt
arXiv:2606.05176v1 Announce Type: new Abstract: While large language models (LLMs) show strong performance in natural language understanding and generation, their evaluation and adaptation to domain-s
arXiv:2606.05759v1 Announce Type: new Abstract: Hyperspectral imaging provides rich spectral information for quantitative remote sensing, yet hyperspectral sensors remain costly and thus unavailable i
arXiv:2606.05744v1 Announce Type: new Abstract: Spatial planning maps are central to territorial governance, translating planning objectives, regulations, and spatial strategies into visual forms for
arXiv:2606.05173v1 Announce Type: new Abstract: Masked language modelling (MLM) has been the dominant pre-training objective for text encoders since BERT, yet it encourages representations that are st
arXiv:2606.05836v1 Announce Type: new Abstract: Large language models have substantially advanced Text-to-SQL systems, yet applying them to enterprise-scale databases remains challenging. Real-world d
arXiv:2605.25956v2 Announce Type: replace Abstract: Urgent suspected colorectal cancer (CRC) referrals create operational bottlenecks because semi-structured clinical documents often require manual re
arXiv:2606.05402v1 Announce Type: new Abstract: Large reasoning models (LRMs) produce reasoning traces with non-linear structures, such as backtracking and self-correction, that complicate the evaluat
arXiv:2606.06027v1 Announce Type: cross Abstract: Community-conditioned language model adaptation requires choices about data collection, community definition, and evaluation that are currently made i
arXiv:2606.05901v1 Announce Type: new Abstract: Large language models (LLMs) have fundamentally transformed the landscape of Natural Language Processing. Despite these advances, LLMs and LLM-based sys
arXiv:2606.05895v1 Announce Type: new Abstract: Research attention is widely used as an indicator of visibility, influence, and societal uptake, yet it is typically represented as aggregated counts th
arXiv:2606.05698v1 Announce Type: new Abstract: Parametric retrieval augmentation encodes document information into lightweight, document-specific modules such as LoRA adapters, reducing the need to i