Knowledge catalogue
arXiv:2609.32810v1 Announce Type: cross Abstract: Multidisciplinary tumor boards integrate multimodal clinical observations and longitudinal patient histories through specialist discussions, yet bench
arXiv:2609.33194v1 Announce Type: new Abstract: Matrix-valued optimizers such as Muon exploit the spectral structure of neural network updates through Newton--Schulz orthogonalization, but their near-
arXiv:2609.34867v1 Announce Type: new Abstract: Vision language models have achieved strong performance across a wide range of multimodal applications, yet their substantial computational and memory c
arXiv:2609.32685v1 Announce Type: cross Abstract: Physics-informed neural networks (PINNs) provide a learning-based framework for solving partial differential equations (PDEs), yet their training beha
arXiv:2609.34415v1 Announce Type: new Abstract: The transition from Large Language Models (LLMs) to agents shifts safety stakes from toxic text to irreversible environmental harm. While current defens
arXiv:2609.33638v1 Announce Type: new Abstract: We introduce RareTrap, a framework for estimating the probability of severe behaviors in black box large language models (LLMs). A key challenge for pro
arXiv:2609.32389v1 Announce Type: new Abstract: Filmmakers and visual artists routinely need to compose multiple references, actors, locations, props, cultural elements, into a single coherent shot, b
arXiv:2609.34177v1 Announce Type: cross Abstract: When an agent reuses logged experience, a changed decision may reflect the recorded score, the action's name, or the record's position in storage. Sta
arXiv:2609.35707v1 Announce Type: new Abstract: Recent progress in machine learning is driven by large-scale foundation models, where scaling laws and finding optimal scaling prescriptions for archite
arXiv:2609.32698v1 Announce Type: new Abstract: Recent vision-language-action (VLA) policies demonstrate promising generalization across diverse short-horizon tasks. However, they remain unreliable on
arXiv:2609.31788v1 Announce Type: new Abstract: Progress in 3D CT report generation is usually sought in increasingly sophisticated architectures and larger pools of training data. We find instead tha
arXiv:2609.34479v1 Announce Type: new Abstract: Vision-language (VL) pretraining using paired chest X-ray (CXR) images and radiology reports has shown strong potential for medical image understanding.
arXiv:2609.35225v1 Announce Type: cross Abstract: Sign language translation and generation share the goal of bidirectional alignment between text and sign representations. However, existing approaches
arXiv:2609.34707v1 Announce Type: new Abstract: Object navigation requires an embodied agent to find an object in an unseen environment under partial observability and a limited motion budget. Existin
arXiv:2609.34088v1 Announce Type: new Abstract: TRACE (Text-Reinforced Analysis of Cardio ECGs) is a multimodal electrocardiogram (ECG) representation model that learns clinically grounded signal embe
arXiv:2609.34539v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) have emerged as the dominant architecture for high-fidelity image and video generation. Recent DiT systems increasingly us
arXiv:2609.34639v1 Announce Type: new Abstract: We study approximate sampling: given N independent samples from a proposal distribution mu, the goal is to select one whose distribution is close to a t
arXiv:2512.17992v2 Announce Type: replace Abstract: Long-horizon robotic tasks are hard due to continuous state-action spaces and sparse feedback. Symbolic world models help by decomposing tasks into
For example, directly using claude code or code, which is then hooked up to automatically delegate the actual code writing tasks to a local model like qwen 3.8 flash next, to save on cloud usage limit
arXiv:2609.34861v1 Announce Type: new Abstract: Visual token pruning has been widely studied as a practical approach to reducing the computational cost of large vision-language models. However, it str
arXiv:2609.34554v1 Announce Type: new Abstract: Memory is essential for long-horizon, partially observed robotic manipulation: a robot must remember which object was placed in a drawer, whose cup it m
arXiv:2609.34065v1 Announce Type: cross Abstract: Names are personal identifiers, but they also carry social meaning and are widely used to evaluate how language models treat different people. Such ev
arXiv:2609.30813v1 Announce Type: new Abstract: Evaluating claim admission in shared agent memory is challenging because repeated claims may be mistaken for independent evidence. An agent may copy or
arXiv:2609.30631v1 Announce Type: cross Abstract: Online audio-visual target-speaker extraction aims to remove competing voices while preserving speech quality and bounding lookahead. Existing extract
arXiv:2609.31260v1 Announce Type: cross Abstract: We investigate the systemic macroscopic dynamics emerging from Limit Order Books (LOBs) populated exclusively by autonomous reinforcement-learning age
arXiv:2609.30725v1 Announce Type: new Abstract: Although effective, coding agents often incur substantial monetary costs. Their recurring cost-inefficient behaviors remain underexplored. We conduct th
arXiv:2609.30541v1 Announce Type: new Abstract: Optimizing embedding systems for production recommendation pipelines demands systematic exploration that consumes disproportionate engineering effort at
context : do not re-reserve the scheduler when toggling causal_attn (#28751) context : do not re-reserve the scheduler when toggling causal_attn llama_context::set_causal_attn() marks the scheduler to
arXiv:2602.02043v2 Announce Type: replace-cross Abstract: Modern vision-language models struggle with basic compositional reasoning, failing to bind attributes to objects or relations to their referen
arXiv:2609.30489v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated historic breakthroughs in general reasoning with early successes in biomedical science. However, existing
arXiv:2609.30293v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) enables AI agents to discover and call tools, but loading every definition becomes expensive as connected catalogs gr
Claude Sonnet 5.5 New Sonnet model from Anthropic today. They say it 'runs 30%+ faster, and costs up to 30% less for most work' - it's priced the same as Sonnet 5 but appears to beat it on every bench
arXiv:2609.30345v1 Announce Type: cross Abstract: Cloud-security investigation is dominated by population tasks: which identities can read a data store, how many resources fail a control, which assets
arXiv:2609.31272v1 Announce Type: cross Abstract: AI is becoming increasingly integrated into daily workflows, especially in computing. We are gradually shifting towards an AI-rich future, an impendin
arXiv:2609.31381v1 Announce Type: new Abstract: Context projection replaces older tool observations with compact, addressable excerpts, reducing repeated input while potentially adding evidence-retrie
arXiv:2609.30974v1 Announce Type: new Abstract: Lexical semantic change is usually summarized by a scalar distance between independently sampled period distributions. This measures how much a word cha
arXiv:2609.31103v1 Announce Type: cross Abstract: Spatial reasoning with metric constraints requires linking objects to geometric measurements and preserving their numerical content during language re
arXiv:2609.30977v1 Announce Type: cross Abstract: Uniform discrete diffusion models (UDMs) commonly use explicit time conditioning, but we find that it can often be unnecessary in practice. In this pa
arXiv:2609.30611v1 Announce Type: cross Abstract: On Jan. 30, 2026, the U.S. Department of Justice released a mixed-media collection concerning Jeffrey Epstein, including about three million pages of
arXiv:2609.30535v1 Announce Type: new Abstract: Children in multilingual communities often code-switch, using multiple languages in a single utterance. Can we induce cross-lingual alignment in languag
arXiv:2602.09163v2 Announce Type: replace Abstract: Scientific knowledge bases accelerate discovery by curating findings from primary literature into structured, queryable formats for both human resea
arXiv:2609.31450v1 Announce Type: cross Abstract: Medical vision-language model (VLM) post-training is commonly evaluated through answer accuracy. We examine how changes in accuracy and training objec
arXiv:2609.31595v1 Announce Type: new Abstract: 3D scene graphs provide a structured representation of complex environments by encoding objects, their semantic attributes, and the spatial and function
arXiv:2609.30326v1 Announce Type: new Abstract: Activation steering changes a model's internal activations during inference without updating its weights, but a useful intervention must determine both
Introducing FireRouter with Opus. Our first router model. Routine tasks go to top open models, Claude Opus handles the rest. Cache and task-aware routing. Proven 98.1% of Opus accuracy with 57% lower
arXiv:2609.30706v1 Announce Type: new Abstract: 'System One' decision models such as TypeSafe's Jev and its open counterpart Laya answer typed questions about a text in a single forward pass with cali
arXiv:2609.30943v1 Announce Type: new Abstract: Long-form technical text generation underpins knowledge-intensive workflows, yet remains challenging for large language models (LLMs) due to the need fo
arXiv:2609.30288v1 Announce Type: new Abstract: In Transformer-based masked language models, attention is the primary mechanism for context mixing, but there are other ways to mix data across tokens.
arXiv:2609.31285v1 Announce Type: new Abstract: Facial micro-expressions are spontaneous, brief, and subtle facial movements that reveal suppressed emotions in high-stakes environments. In contrast to
arXiv:2609.30609v1 Announce Type: new Abstract: Multi-shot agentic video generation requires consistent character appearance, stable spatial layout across camera angles, and continuous character state
arXiv:2609.31255v1 Announce Type: new Abstract: General-purpose agent memory summarizes conversations: it extracts salient snippets, embeds them, and retrieves the top-k into the prompt. A health agen
arXiv:2609.30657v1 Announce Type: cross Abstract: Large language model email assistants are particularly vulnerable to indirect prompt injection because untrusted email content can be retrieved into t
arXiv:2609.31505v1 Announce Type: new Abstract: Despite the growing capabilities of large language models (LLMs), prompt design remains largely heuristic and ad hoc. This project will explore extit{pr
arXiv:2609.30578v1 Announce Type: new Abstract: Language models gain accuracy from more compute at test time, but majority voting over independent samples saturates: as samples grow, the vote converge
arXiv:2609.30918v1 Announce Type: cross Abstract: Robust counterfactual explanations promise recourse that still works after the model behind it changes. Whether they keep that promise depends on what
arXiv:2609.30295v1 Announce Type: cross Abstract: Identifying an unfamiliar sign is difficult when a learner remembers its movement but does not know its meaning or formal feature codes. SignTrace add
arXiv:2609.31607v1 Announce Type: cross Abstract: Generative AI systems are increasingly used, but aligning their outputs with user requirements poses a continuing challenge. Here, we aim to ensure th
arXiv:2609.30383v1 Announce Type: new Abstract: A skill is a modular package of natural-language instructions, executable scripts, and reference resources that an agent can load at runtime to extend i
arXiv:2605.06642v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used as interactive agents, but optimizing them for long-horizon decision making remains difficu
arXiv:2609.31524v1 Announce Type: new Abstract: Surgical scene understanding is critical for computer-assisted intervention, yet laparoscopic cholecystectomy remains challenged by the complex anatomy