Knowledge catalogue
arXiv:2608.01772v2 Announce Type: replace Abstract: LLM agents increasingly run policy-bound enterprise workflows, where they must apply rules consistently and stay auditable. Deploying such an agent
arXiv:2610.01000v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used as probabilistic generators for simulation, synthetic data generation, and decision support in settin
arXiv:2610.01527v1 Announce Type: cross Abstract: Non-Markovian environments are often modeled as Regular Decision Processes (RDPs), where dynamics depend on the interaction history through a finite a
arXiv:2610.00394v1 Announce Type: new Abstract: This paper studies forking, a generalization failure discovered in NanoGPT autoresearch. Under data replay, models with an over-encoding n-gram memory b
arXiv:2610.01181v1 Announce Type: new Abstract: We consider stochastic games with independent controlled chains and unknown transition kernels, where players observe only their local states and realiz
Whether you’re launching microservices in response to sudden traffic spikes, deploying new software releases, or scaling up application replicas, pod startup time is critical to maintaining a fast, re
arXiv:2610.02186v1 Announce Type: cross Abstract: Molecular learning models are strongly shaped by their underlying representations. Yet standard sequential and graph formalisms struggle to explicitly
arXiv:2505.22767v4 Announce Type: replace-cross Abstract: Dialogue with a large language model can lead a person to insight: a sudden change in how they understand a problem. This perspective asks how
Ahmad Al‑Dahle joined Airbnb as CTO in January 2026 after leading Meta’s Llama generative‑AI models (2023–2025). He is steering an “inside‑out AI” strategy that deploys internal AI tools—such as the c
arXiv:2610.00615v1 Announce Type: new Abstract: One might think that learning the identity function with a deep linear residual network is trivial - the path along residual connections already impleme
arXiv:2610.00755v1 Announce Type: cross Abstract: There is considerable interest in using time-varying electricity prices to shape consumer demand response, and better align energy demand with renewab
arXiv:2610.00881v1 Announce Type: new Abstract: Sign language machine translation has progressed substantially over the past decade, evolving from isolated sign recognition to end-to-end translation s
arXiv:2610.00902v1 Announce Type: cross Abstract: One way to make AI systems safe is to shape what the system is: its objective and dispositions. We take a complementary route: treat the agents' chara
arXiv:2607.15942v2 Announce Type: replace Abstract: Remote sensing vision-language models are increasingly expected to support open-ended reasoning over Earth Observation data and a variety of tasks.
arXiv:2610.00672v1 Announce Type: new Abstract: Protein foundation models support mutation-effect and structural prediction, but predictive performance alone does not reveal which forms of biological
arXiv:2610.00737v1 Announce Type: cross Abstract: Personalized image generation has remained narrowly focused on conditional synthesis from curated visual exemplars, rather than capturing who a user i
arXiv:2610.01356v1 Announce Type: new Abstract: Stable port-Hamiltonian neural networks certify asymptotic stability by construction. Yet, their Hamiltonian is a global Lyapunov function with a single
arXiv:2610.01554v1 Announce Type: new Abstract: Wanda (Sun et al., 2024) prunes large language models by scoring weights independently within each linear projection, although queries and keys interact
arXiv:2610.00526v1 Announce Type: cross Abstract: In-context learning (ICL) can be amortized into latent objects (task vectors, function vectors, context vectors) that recover few-shot behavior at zer
arXiv:2610.01283v1 Announce Type: new Abstract: Reliable shelf monitoring is an important capability for retail automation, yet existing out-of-stock detection methods mainly operate in image space an
arXiv:2610.00395v1 Announce Type: new Abstract: Inference-time steering enables pretrained diffusion models to satisfy new constraints without full retraining. However, specificity-aware generation is
arXiv:2610.01438v1 Announce Type: new Abstract: Unmanned aerial vehicle (UAV) photogrammetry is increasingly used in applications requiring high accuracy, such as determining ground surface changes ca
arXiv:2606.14597v2 Announce Type: replace Abstract: Transformer-based neural operators have shown remarkable performance for approximating solution operators of partial differential equations on compl
arXiv:2607.11555v2 Announce Type: replace Abstract: Learning neural set functions is pivotal to a wide range of important applications, including compound selection in AI-driven drug discovery and pro
AI agent infrastructure is evolving to support systems that move continuously among inference, feedback and training. Cognition AI Inc.’s Devin now assists throughout the software development lifecycl
arXiv:2609.39408v1 Announce Type: new Abstract: Population loss can remain nearly constant while a neural network learns a substantially more predictive representation. We establish this separation fo
arXiv:2609.38901v1 Announce Type: new Abstract: Representer explanations rank the training landmarks that most influence a self-supervised representation. At scale, this ranking rests on up to four st
Optional Bundle architecture: Schedule (session-local delayed / timed / interval reminders) was removed from the default set and made an explicit Optional Bundle. This cleanly separates “installed” fr
arXiv:2609.40292v1 Announce Type: new Abstract: How is computation organized and reused across tasks and time in a trained recurrent network? Most analyses emphasize the geometry of neural activity, d
arXiv:2609.39284v1 Announce Type: cross Abstract: While large language models have achieved remarkable success in isolated code generation, authentic software engineering requires sustained reasoning,
arXiv:2511.10796v2 Announce Type: replace-cross Abstract: The empirical state-space Neural Tangent Kernel (NTK) describes the local learning geometry of a finite-width neural network, but computing it
arXiv:2609.38594v1 Announce Type: new Abstract: Group synchronization (GS) is the problem of estimating a set of N unknown elements g_1,ldots, g_N in G in a group G, given noisy measurements of a subs
arXiv:2609.39634v1 Announce Type: cross Abstract: Common policy improvement methods, including TRPO, PPO, and GRPO, estimate policy improvement under the behavioral policy's state-visitation distribut
arXiv:2609.40181v1 Announce Type: new Abstract: We introduce Index-Translate, a multilingual translation model family that combines a shared multilingual foundation with specialized training for gener
arXiv:2609.39361v1 Announce Type: new Abstract: While most attention logits can be computed in low precision without degrading numerical stability, current attention kernels fail to exploit this pheno
arXiv:2410.02343v2 Announce Type: replace Abstract: Large language models (LLMs) routinely fail to output the correct option in multiple-choice question answering (MCQA) while encoding the answer inte
arXiv:2609.39185v1 Announce Type: new Abstract: Mamba-style and hybrid language models compress their past into a fixed-size recurrent state that is rewritten at every generated token. Storing this st
arXiv:2410.02159v3 Announce Type: replace-cross Abstract: Language models (LMs) can 'memorize' information, i.e., encode training data in their weights in such a way that inference-time queries can le
arXiv:2609.39291v1 Announce Type: new Abstract: Physics-informed computational methods usually optimize parameters within a functional representation whose structure is fixed in advance. This work pro
arXiv:2609.39223v1 Announce Type: new Abstract: Large language model (LLM) inference is increasingly moving toward lower precision to realize the throughput of hardware accelerators, but aggressive po
arXiv:2609.39164v1 Announce Type: new Abstract: Score-based variational inference (VI) provides an alternative to Kullback--Leibler (KL)-based VI by minimizing the Fisher divergence between the variat
arXiv:2609.38265v1 Announce Type: cross Abstract: Onboard AI is gaining interest for space applications such as vessel, wildfire, and cloud detection, where real-time processing can improve mission re
arXiv:2609.38538v1 Announce Type: cross Abstract: Random splitting can yield non-independent train--test subsets when a dataset contains related samples, as is common in certain applications such as b
arXiv:2310.11379v2 Announce Type: replace-cross Abstract: Voice-based interfaces rely on a wake-up word mechanism to initiate communication with devices. However, achieving a robust, energy-efficient,
arXiv:2609.38521v1 Announce Type: cross Abstract: We introduce ShamAN-Q, a sub-1-bit post-training quantization method that extends NanoQuant by replacing each its diagonal reconstruction geometry wit
arXiv:2603.02561v2 Announce Type: replace-cross Abstract: Attention mechanism remains the defining operator in Transformers since it provides expressive global credit assignment, yet its quadratic cos
arXiv:2609.38612v1 Announce Type: new Abstract: As natural language drives more applications, language models increasingly run inside programs as decision components: the program sends them the curren
arXiv:2609.38565v1 Announce Type: new Abstract: Over the past 25 years, sketching and sampling have become widely used tools for accelerating large-scale regression. In iterative randomized solvers, a
arXiv:2603.21144v2 Announce Type: replace-cross Abstract: This paper proposes a new formulation of functional Gaussian Process regression on manifolds, based on an Empirical Bayes approach, in the spa
arXiv:2609.40356v1 Announce Type: cross Abstract: Recent video generation is increasingly realistic and controllable, yet video editing remains less developed, particularly for precise local edits tha
Volantis Inc. today announced that it has raised a 88 million funding round led by prominent angel investor Lachy Groom and Abstract Ventures. The Series A deal also drew more than a half-dozen other
arXiv:2609.35886v1 Announce Type: cross Abstract: AI agents now hold spend authority and settle payments without per-action human confirmation. The resulting loss is often not a security failure: a co
arXiv:2601.08777v2 Announce Type: replace-cross Abstract: Aligning large language models (LLMs) to serve users with heterogeneous and potentially conflicting preferences is a central challenge for per
'AREX-2 is a 27B-parameter long-horizon agent model from the Beijing Academy of Artificial Intelligence (BAAI). It learns to improve a solution over multiple test-time rounds: propose, measure, reflec
Our agent workflow is currently executing a group of 10 vllm api calls within a asyncio.gather we made them share the same prompt until the end where the queries/instruction prompts differ. These call
arXiv:2609.35841v1 Announce Type: cross Abstract: Mutation testing evaluates test-suite adequacy by injecting synthetic faults into program code. However, traditional rule-based tools often generate l
arXiv:2609.36730v1 Announce Type: new Abstract: Agents increasingly build on code written by other agents, and they reimplement rather than reuse, growing the codebases later agents must work in. To m
arXiv:2609.36240v1 Announce Type: new Abstract: Does representation learning stop when the training loss stops improving? We study this question for matrix Muon, whose polar-normalised updates have a
arXiv:2609.35883v1 Announce Type: cross Abstract: Genome foundation models are growing into sparse mixture-of-experts (MoE) networks whose expert weights no longer fit on the machines that hold the se
arXiv:2609.36752v1 Announce Type: new Abstract: Circuit design is a complex and iterative process that requires expertise in electronic engineering. It involves selecting components while meeting perf