Knowledge catalogue
arXiv:2604.11759v1 Announce Type: new Abstract: Organizational knowledge used by AI agents typically lacks epistemic structure: retrieval systems surface semantically relevant content without distingu
arXiv:2604.10695v1 Announce Type: new Abstract: Recent Audio-Visual Question Answering (AVQA) methods have advanced significantly. However, most AVQA methods lack effective mechanisms for handling mis
arXiv:2604.11496v1 Announce Type: cross Abstract: Dual-encoder Vision-Language Models (VLMs) such as CLIP are often characterized as bag-of-words systems due to their poor performance on compositional
arXiv:2505.24778v3 Announce Type: replace Abstract: As large language models (LLMs) are increasingly used in high-stakes domains, accurately assessing their confidence is crucial. Humans typically exp
arXiv:2604.09991v1 Announce Type: new Abstract: Infrared small target detection still faces two persistent challenges: training instability from non-monotonic scale loss functions, and inadequate spat
arXiv:2604.10916v1 Announce Type: cross Abstract: Ultrasound acquisition requires skilled probe manipulation and real-time adjustments. Vision-language models (VLMs) could enable autonomous ultrasound
arXiv:2604.10183v1 Announce Type: cross Abstract: Wireless sensing, traditionally relying on signal processing (SP) techniques, has recently shifted toward data-driven deep learning (DL) to achieve pe
arXiv:2604.07512v2 Announce Type: replace Abstract: We present Rhizome OS-1, a semi-autonomous operating system for small molecule drug discovery in which multi-modal AI agents operate as a full multi
arXiv:2601.08039v2 Announce Type: replace Abstract: In this paper, we study Riemannian zeroth-order optimization in settings where the underlying Riemannian metric g is geodesically incomplete, and th
arXiv:2509.21982v2 Announce Type: replace Abstract: E-commerce risk management requires aggregating diverse, deeply embedded web data through multi-step, stateful interactions, which traditional scrap
arXiv:2602.03402v3 Announce Type: replace Abstract: Vision language models (VLMs) extend the reasoning capabilities of large language models (LLMs) to cross-modal settings, yet remain highly vulnerabl
arXiv:2410.13987v3 Announce Type: replace Abstract: Answering complex real-world questions in the medical domain often requires accurate retrieval from medical Textual Knowledge Graphs (medical TKGs),
arXiv:2604.03768v2 Announce Type: replace Abstract: Unsustainable land-use practices in ecologically sensitive regions threaten biodiversity, water resources, and the livelihoods of millions. This pap
arXiv:2510.16333v2 Announce Type: replace Abstract: A dominant assumption in Multimodal Language Model (MLLM) research is that its performance is largely inherited from the LLM backbone, given its imm
This article by @rmaruy explores whether discrete code or symbol systems can spontaneously emerge within a single neural network, examining the conditions under which internal representations might de
arXiv:2604.10929v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) provide robots with contextual reasoning abilities to comprehend human instructions. Yet, current LLM-en
arXiv:2511.17441v3 Announce Type: replace Abstract: Despite the critical role of bimanual manipulation in endowing robots with human-like dexterity, large-scale and diverse datasets remain scarce due
arXiv:2604.09860v1 Announce Type: cross Abstract: The pursuit of general-purpose robotics has yielded impressive foundation models, yet simulation-based benchmarking remains a bottleneck due to rapid
arXiv:2603.12639v2 Announce Type: replace Abstract: Scalable Embodied AI faces fundamental constraints due to prohibitive costs and safety risks of real-world interaction. While Embodied World Models
arXiv:2604.10974v1 Announce Type: new Abstract: Reinforcement learning (RL) policies often fail under dynamics that differ from training, a gap not fully addressed by domain randomization or existing
arXiv:2604.09710v1 Announce Type: new Abstract: Automated diagnosis from chest CT has improved considerably with deep learning, but models trained on skewed datasets tend to perform unevenly across pa
arXiv:2508.21322v2 Announce Type: replace Abstract: Achieving both safety guarantees and real-time performance in cooperative vehicle coordination remains a fundamental challenge, particularly in dyna
arXiv:2604.09814v1 Announce Type: new Abstract: Medical image segmentation models built on Segment Anything Model (SAM) achieve strong performance on clean benchmarks, yet their reliability often degr
arXiv:2505.09368v2 Announce Type: replace Abstract: Standard benchmarks for optical flow, scene flow, and stereo vision algorithms generally focus on model accuracy rather than robustness to image cor
arXiv:2604.11655v1 Announce Type: cross Abstract: The rapid adoption of Large Language Models (LLMs) in interactive systems has enabled the creation of dynamic, open-ended Role-Playing Agents (RPAs).
arXiv:2604.11156v1 Announce Type: new Abstract: Unsupervised remote photoplethysmography (rPPG) promises to leverage unlabeled video data, but its potential is hindered by a critical challenge: traini
arXiv:2604.11037v1 Announce Type: cross Abstract: Multi-step agentic reinforcement learning benefits from fine-grained credit assignment, yet existing approaches offer limited options: critic-free met
arXiv:2604.11233v1 Announce Type: new Abstract: Lemmatization -- the task of mapping an inflected word form to its dictionary form -- is a crucial component of many NLP applications. In this paper, we
This r/ollama community thread discusses practical strategies for managing context windows when using locally-run LLMs (via Ollama) for coding assistance on large codebases, where context limitations
arXiv:2604.11315v1 Announce Type: cross Abstract: We introduce the Structured Sparsity Specification (S^3), an algebraic framework for defining, composing, and implementing structured sparse patterns.
arXiv:2503.05534v3 Announce Type: replace Abstract: Purpose: The Segment Anything Model (SAM) promises to ease the annotation bottleneck in medical segmentation, but overlapping anatomy and blurred bo
arXiv:2604.11803v1 Announce Type: new Abstract: Natural language processing (NLP) and speech technologies have made significant progress in recent years; however, they remain largely focused on standa
arXiv:2604.11447v1 Announce Type: new Abstract: Ensuring operational safety is critical for human-to-humanoid motion imitation. This paper presents a vision-based framework that enables a humanoid rob
arXiv:2508.11290v3 Announce Type: replace Abstract: LLMs increasingly exhibit over-refusal behavior, where safety mechanisms cause models to reject benign instructions that seemingly resemble harmful
arXiv:2604.10429v1 Announce Type: new Abstract: This paper considers the problem of zero-shot safety guarantees for cascade dynamical systems. These are systems where a subset of the states (the inner
【採用情報】Sakana AIで「Project Manager（製造分野）」を募集🐟 https://sakana.ai/careers/#business-role-project-manager-manufacturing エンジニア・リサーチャーと協働して製造現場の困難な課題をAIで解き、Go-To-Market戦略も担う重要ポジションです。 このようなご経験をお持ちの方を募集 ・大手製造
☁️ Salesforce tools now in Fleet One of the most requested features we've gotten, and it's now a first-class supported tool in Fleet! Just sign in with your Salesforce account, and start using it imme
Adrian Diaconescu / PhoneArena: Samsung quietly increases US prices of the Galaxy S25 Edge, S25 FE, Z Flip 7, Tab S11, Tab S11 Ultra, and more; the 1TB Galaxy Tab S11 Ultra jumps by $280 — Some of the
arXiv:2604.11003v1 Announce Type: new Abstract: Agentic data science (ADS) pipelines have grown rapidly in both capability and adoption, with systems such as OpenAI Codex now able to directly analyze
arXiv:2505.13777v2 Announce Type: replace-cross Abstract: We present Sat2Sound, a unified multimodal framework for geospatial soundscape understanding, designed to predict and map the distribution of
arXiv:2604.10306v1 Announce Type: new Abstract: As Earth-observation workloads move toward onboard and edge processing, remote-sensing segmentation models must operate under tight latency and energy c
arXiv:2511.12022v2 Announce Type: replace Abstract: Autonomous robots operating in dynamic environments must balance global path optimality with real-time responsiveness to disturbances. This requires
arXiv:2512.19691v3 Announce Type: replace Abstract: Reference labels for machine-learning benchmarks are increasingly synthesized with LLM assistance, but their reliability remains underexamined. We a
We share Cloudflare's internal strategy for governing MCP using Access, AI Gateway, and MCP server portals. We also launch Code Mode to slash token costs and recommend new rules for detecting Shadow M
Over 80% of enterprise data lives in unstructured form — PDFs, emails, reports, regulatory filings. Most of the time, such sources contain critical business information, yet they remain difficult to a
arXiv:2512.12982v2 Announce Type: replace Abstract: The pursuit of a universal AI-generated image (AIGI) detector often relies on aggregating data from numerous generators to improve generalization. H
arXiv:2604.11402v1 Announce Type: new Abstract: Scene change detection (SCD) is crucial for urban monitoring and navigation but remains challenging in real-world environments due to lighting variation
Ollama posted a social media announcement on X promoting an event that requires both an RSVP and approval to attend, with registration available through a Luma event page linked to an Ollama and Gemma
arXiv:2511.18329v3 Announce Type: replace Abstract: Scientific posters play a vital role in academic communication by presenting ideas through visual summaries. Analyzing reading order and parent-chil
arXiv:2604.10718v1 Announce Type: new Abstract: Accelerating scientific discovery requires the identification of which experiments would yield the best outcomes before committing resources to costly p
arXiv:2307.01139v2 Announce Type: replace-cross Abstract: Instruction finetuning is a popular paradigm to align large language models (LLM) with human intent. Despite its popularity, this idea is less
arXiv:2604.05489v3 Announce Type: replace Abstract: Text-to-Video (T2V) generation has benefited from recent advances in diffusion models, yet current systems still struggle under complex scenarios, w
arXiv:2604.11625v1 Announce Type: cross Abstract: Neural operators have emerged as powerful surrogates for partial differential equation (PDE) solvers, yet they are typically trained as monolithic mod
arXiv:2512.12675v2 Announce Type: replace-cross Abstract: Subject-driven image generation has advanced from single- to multi-subject composition, while neglecting distinction, the ability to distingui
arXiv:2604.10688v1 Announce Type: cross Abstract: On-policy reinforcement learning has become the dominant paradigm for reasoning alignment in large language models, yet its sparse, outcome-level rewa
arXiv:2604.10962v1 Announce Type: new Abstract: Flow Matching (FM) policies have emerged as an efficient backbone for robotic control, offering fast and expressive action generation that underpins rec
arXiv:2412.07469v3 Announce Type: replace-cross Abstract: Causal discovery is a crucial initial step in establishing causality from empirical data and background knowledge. Numerous algorithms have be
arXiv:2604.11244v1 Announce Type: new Abstract: Advances in Multimodal Large Language Models (MLLMs) are transforming video captioning from a descriptive endpoint into a semantic interface for both vi
arXiv:2604.09743v1 Announce Type: cross Abstract: Multi-modal image registration plays a critical role in precision medicine but faces challenges from non-linear intensity relationships and local opti
arXiv:2604.07791v2 Announce Type: replace Abstract: Recent advances in Reinforcement Learning with Verifiable Rewards (RLVR) have demonstrated significant potential in single-turn reasoning tasks. Wit