Knowledge catalogue
arXiv:2411.00361v4 Announce Type: replace Abstract: Hierarchical reinforcement learning (HRL) enables agents to solve complex, long-horizon tasks by decomposing them into manageable sub-tasks. However
arXiv:2510.26109v4 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards (RLVR) has significantly boosted the reasoning capability of language models (LMs). However, existing
arXiv:2604.14747v1 Announce Type: new Abstract: Solving non-linear least-squares problem for pose estimation (rotation and translation) is often a time consuming yet fundamental problem in several rea
arXiv:2604.14849v1 Announce Type: new Abstract: Purpose: Adaptive skip modules can improve medical image segmentation, but searching for them is computationally costly. Implantable Adaptive Cells (IAC
arXiv:2601.03448v2 Announce Type: replace Abstract: Language models (LMs) are pre-trained on raw text datasets to generate text sequences token-by-token. While this approach facilitates the learning o
arXiv:2602.12389v3 Announce Type: replace-cross Abstract: Temporal knowledge graph (TKG) forecasting requires predicting future facts by jointly modeling structural dependencies within each snapshot a
arXiv:2604.14640v1 Announce Type: new Abstract: The proliferation of financial misinformation poses a severe threat to market stability and investor trust, misleading market behavior and creating crit
arXiv:2604.06647v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) systems are typically evaluated under static assumptions, despite being frequently corrected through user or ex
arXiv:2604.14933v1 Announce Type: new Abstract: Skeleton-based human action recognition is a powerful approach for understanding human behaviour from pose data, but collecting large-scale, diverse, an
arXiv:2604.14166v1 Announce Type: new Abstract: Mapping Cyber Threat Intelligence (CTI) text to MITRE ATT&CK technique IDs is a critical task for understanding adversary behaviors and automating threa
A guide on disabling thinking mode in Ollama models using the CLI by running models with the `--think=false` flag or using `/set nothink` followed by a prompt. The post likely discusses how to configu
arXiv:2509.23638v2 Announce Type: replace Abstract: Mixture-of-Experts (MoE) models face memory and PCIe latency bottlenecks when deployed on commodity hardware. Offloading expert weights to CPU memor
arXiv:2604.14562v1 Announce Type: new Abstract: Accurate thermal modeling in metal additive manufacturing (AM) is essential for understanding the process-structure-performance relationship. While prio
arXiv:2604.14565v1 Announce Type: new Abstract: Embodiment is a significant keyword in recent machine learning fields. This study focused on the passive nature of the body of a biped robot to generate
arXiv:2604.14825v1 Announce Type: cross Abstract: We present Nautilus, a novel tensor compiler that moves toward fully automated math-to-kernel optimization. Nautilus compiles a high-level algebraic s
arXiv:2604.14953v1 Announce Type: new Abstract: Gesture recognition research, unlike NLP, continues to face acute data scarcity, with progress constrained by the need for costly human recordings or im
arXiv:2604.14634v1 Announce Type: new Abstract: Multiple choice evaluation is widely used for benchmarking large language models, yet near ceiling accuracy in low option settings can be sustained by s
arXiv:2507.18454v2 Announce Type: replace-cross Abstract: CPUs are critical for LLM serving due to their availability, cost efficiency, and edge applicability. However, efficient CPU serving is hinder
arXiv:2604.14941v1 Announce Type: new Abstract: Communicating complex system designs or scientific processes through text alone is inefficient and prone to ambiguity. A system that automatically gener
arXiv:2604.14619v1 Announce Type: cross Abstract: In computational paralinguistics, detecting cognitive load and deception from speech signals is a heavily researched domain. Recent efforts have attem
arXiv:2604.15301v1 Announce Type: new Abstract: Many SLT systems quietly assume that brief chunks of signing map directly to spoken-language words. That assumption breaks down because signers often cr
arXiv:2604.14749v1 Announce Type: new Abstract: Large language models still struggle with faithfulness and hallucinations despite their remarkable reasoning abilities. In Knowledge Graph Question Answ
arXiv:2510.23853v3 Announce Type: replace Abstract: Large language model (LLM) agents are increasingly used to interact with and execute tasks in dynamic environments. However, a critical yet overlook
arXiv:2604.13367v1 Announce Type: new Abstract: Radiotherapy-induced normal tissue injury is a clinically important complication, and accurate segmentation of injury regions from medical images could
arXiv:2604.13397v1 Announce Type: new Abstract: Proton therapy offers superior organ-at-risk sparing but is highly sensitive to anatomical changes, making accurate deformable image registration (DIR)
Oliver Whang / New York Times: A primer on “interpretability” and how AI researchers are figuring out how to open and understand the “black box” that holds the formulas within most AI models — When De
arXiv:2604.13133v1 Announce Type: new Abstract: Thermodynamic cycles are pivotal in determining the efficacy of energy conversion systems. Traditional design methodologies, which rely on expert knowle
This Reddit thread discusses running Ollama on a resource-constrained 8GB CPU-only ARM VPS, addressing common challenges such as out-of-memory errors and model response looping. For purely CPU-only se
arXiv:2604.13061v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in high-stakes autonomous and interactive workflows, where reliability demands continuous, multi-
arXiv:2506.20083v4 Announce Type: replace Abstract: Integrating compositional and symbolic properties into current distributional semantic spaces can enhance the interpretability, controllability, com
arXiv:2604.13634v1 Announce Type: new Abstract: Speculative decoding accelerates autoregressive generation by letting draft tokens bypass full verification, but conventional frameworks suffer from fre
Yes, Ollama models can be used with the Codex app on Windows. Ollama supports all major operating systems, including Windows , and open models can be used with OpenAI's Codex CLI through Ollama — Code
Certinia Inc. wants to transform the professional services industry with artificial intelligence — tasking teams of AI agents to work alongside employees. The company operates a Salesforce-native clou
arXiv:2604.13561v1 Announce Type: new Abstract: Vision-language models trained with contrastive learning on paired medical images and reports show strong zero-shot diagnostic capabilities, yet the eff
arXiv:2604.13761v1 Announce Type: new Abstract: Sparse mixture-of-experts (MoE) layers have been shown to substantially increase model capacity without a proportional increase in computational cost an
arXiv:2603.00192v2 Announce Type: replace Abstract: In healthcare, predictive models increasingly inform patient-level decisions, yet little attention is paid to the variability in individual risk est
arXiv:2604.13902v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has catalyzed significant advances in the reasoning capabilities of Large Language Models (LLMs).
arXiv:2604.13491v1 Announce Type: new Abstract: With the rapid progress of Multimodal Large Language Models (MLLMs), unified MLLMs that jointly perform image understanding and generation have advanced
arXiv:2604.13327v1 Announce Type: cross Abstract: Modern GPU workloads, especially large language model (LLM) inference, suffer from kernel launch overheads and coarse synchronization that limit inter
arXiv:2601.08605v2 Announce Type: replace Abstract: Experience intervention in web agents emerges as a promising technical paradigm, enhancing agent interaction capabilities by providing valuable insi
arXiv:2604.13453v1 Announce Type: new Abstract: Traffic forecasting requires modeling complex temporal dynamics and long-range spatial dependencies over large sensor networks. Existing methods typical
arXiv:2604.13667v1 Announce Type: new Abstract: DNA-based storage has emerged as a promising approach to the global data crisis, offering molecular-scale density and millennial-scale stability at low
Google LLC’s Android team is introducing new ways to build high-quality software for its mobile platform with artificial intelligence agents. Today, the company provided two new tool suites, including
arXiv:2604.05808v2 Announce Type: replace-cross Abstract: Large language model (LLM) agents have demonstrated strong capabilities in complex interactive decision-making tasks. However, existing LLM ag
A community member shared a project on r/ollama (posted in Spanish) announcing the creation of a custom FUSE (Filesystem in Userspace) implementation designed to work with Ollama, the popular local LL
arXiv:2604.14111v1 Announce Type: new Abstract: Large Language Models (LLMs) are now capable of generating highly fluent, human-like text. They enable many applications, but also raise concerns such a
arXiv:2604.13386v1 Announce Type: new Abstract: Linear probes can detect when language models produce outputs they 'know' are wrong, a capability relevant to both deception and reward hacking. However
arXiv:2601.02902v2 Announce Type: replace-cross Abstract: Symbolic logical reasoning is a critical yet underexplored capability of large language models (LLMs), providing reliable and verifiable decis
Lua Global Inc. today announced it raised 5.8 million in early-stage funding to build a platform that allows any team, irrespective of its technical depth, to build, deploy and manage an agentic artif
arXiv:2604.13062v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have demonstrated strong capabilities in code generation and text synthesis, yet their potential for sym
arXiv:2604.13695v1 Announce Type: new Abstract: Reliable and interpretable decision-making is essential in medical imaging, where diagnostic outcomes directly influence patient care. Despite advances
Need to secure your production agents? @Cisco AI Defense Runtime Protection can integrate into your LangChain agents through middleware and produce a consistent runtime contract. 📄 What you need to kn
arXiv:2604.13235v1 Announce Type: new Abstract: Digital elevation modeling of planetary surfaces is essential for studying past and ongoing geological processes. Wide-angle imagery acquired during spa
arXiv:2604.14073v1 Announce Type: new Abstract: Resolving and rewriting references is fundamental in programming languages. Motivated by a real-world decompilation task, we abstract reference rewritin
arXiv:2604.13073v1 Announce Type: new Abstract: Modern multimodal large language models (MLLMs) generate fluent responses from interleaved text, image, audio, and video inputs. However, identifying wh
arXiv:2604.14149v1 Announce Type: new Abstract: Long video understanding is inherently challenging for vision-language models (VLMs) because of the extensive number of frames. With each video frame ty
arXiv:2604.13294v1 Announce Type: new Abstract: Existing video coding for machines is often trained for a specific downstream task and model. As a result, the compressed representation becomes tightly
arXiv:2604.13074v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) serve as daily assistants for millions. However, their ability to generate responses aligned with individual pr
arXiv:2604.14054v1 Announce Type: cross Abstract: Deep search agents have emerged as a promising paradigm for addressing complex information-seeking tasks, but their training remains challenging due t
arXiv:2512.10696v2 Announce Type: replace-cross Abstract: Procedural memory enables large language model (LLM) agents to internalize 'how-to' knowledge, theoretically reducing redundant trial-and-erro