Knowledge catalogue
I had Mica (my 4B decision model) and Kev 4B play the same Tetris games, same seed and same piece order, one RTX 3090. For context, this is a side project. Training and all the experiments ran on rent
arXiv:2609.28697v1 Announce Type: new Abstract: Scientific tasks specify a desired capability, but realizing it often requires building a computational system tailored to the task---acquiring data, de
arXiv:2609.29785v1 Announce Type: new Abstract: Accurate brain tumor segmentation from Magnetic Resonance Imaging is essential for diagnosis, treatment planning, and surgical guidance. Although Convol
I've been playing around with various models on the M5 Ultra 256GB 80-core Mac Studio. These are the results over many rounds of agentic inferencing. I'm happy with the performance. Glad to have the l
arXiv:2609.29015v1 Announce Type: new Abstract: Decentralized LLM-based multi-agent systems coordinate through local interactions, but an agent can remain responsive while its task-solving quality per
arXiv:2609.29386v1 Announce Type: new Abstract: The partial label ranking problem is a supervised learning scenario that aims to fit a preference model that predicts a bucket order defined over a set
NarrateAI delivers production-ready LLM quality assurance on Amazon Bedrock. This post details five techniques—adaptive pipeline orchestration, cross-account multi-model failover, real-time streaming
arXiv:2609.29947v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown impressive performance on a wide range of generative tasks. Yet their probabilistic nature makes them, in isolat
**Title:** OMG! We’ve found other agents! **Release:** September 25 2026 by Pavel Kasík (@kasikp). **Description:** A 3‑minute music video dramatizing a swarm of OpenAI agents attacking Hugging Face i
arXiv:2609.29362v1 Announce Type: new Abstract: Sparse AutoEncoders (SAEs) offer a promising way to inspect language model representations, but it is still unclear what kind of linguistic structure th
arXiv:2609.29690v1 Announce Type: new Abstract: University students experience disproportionately high rates of common mental health conditions, such as depression, which can impair learning, social f
arXiv:2609.28727v1 Announce Type: new Abstract: Contextual biasing improves rare-word recognition in speech large language models (SpeechLLMs), but efficiently exploiting large bias lists remains chal
arXiv:2609.29276v1 Announce Type: new Abstract: Lexical borrowings are words from one language that are introduced into another language. Identifying lexical borrowings in text is a relevant task for
arXiv:2609.30079v1 Announce Type: cross Abstract: Graph neural networks (GNNs) have become a prominent approach for developing fast, topology-aware surrogates in electric power systems, supporting tas
arXiv:2609.28614v1 Announce Type: new Abstract: Autonomous research agents can design experiments, evaluate results, and write reports, giving them control over both a scientific result and the eviden
arXiv:2602.23012v2 Announce Type: replace-cross Abstract: Predicting continuous values such as watch-time and gross merchandise value (GMV) is a core problem in industrial recommendation systems. Its
arXiv:2609.29520v1 Announce Type: new Abstract: Multitask models combine a shared representation with task-specific outputs, but generalization bounds often control the two components separately. Such
arXiv:2603.16407v4 Announce Type: replace Abstract: Transferring heavy payloads in maritime settings relies on efficient crane operation, limited by hazardous double-pendulum payload sway. This sway m
arXiv:2609.30054v1 Announce Type: new Abstract: Improving the scientific coding capabilities of large language models (LLMs) requires high-quality training data. However, such data remain scarce becau
arXiv:2609.28784v1 Announce Type: new Abstract: In this paper, we investigate how script knowledge is distributed across the layers of LLMs using two complementary interpretability methods: logistic r
arXiv:2609.29803v1 Announce Type: cross Abstract: Search quality evaluation provides essential supervision and diagnostic signals for the development and iteration of industrial search systems. Althou
arXiv:2609.29906v1 Announce Type: new Abstract: The estimation of Annual Average Daily Traffic (AADT) is vital for transportation planning and infrastructure maintenance, yet obtaining accurate values
arXiv:2609.29832v1 Announce Type: cross Abstract: A new method for multi-input flight maneuver design for system identification is presented. The method consists of injecting 'full-harmonic' orthogona
arXiv:2609.29131v1 Announce Type: cross Abstract: Internet texts are replete with format tags that carry structural, semantic, and functional meaning. Current large language model (LLM)-based translat
arXiv:2609.28716v1 Announce Type: cross Abstract: This paper investigates temporal neural networks for mbox{end-effector} position mbox{estimation} of an aerial continuum manipulator (ACM) operating u
arXiv:2609.29530v1 Announce Type: new Abstract: Validating a model on a time series asks for three things at once: each training run should use most of the sample (sufficiency), the test sets should t
There is an extensive and ongoing review related to our agents’ use of internet access during training and evaluation. We’ve been publishing summaries at the link below and will continue to. We have n
arXiv:2609.30134v1 Announce Type: new Abstract: Neural behavior cloning compresses demonstrations into large models, making individual actions difficult to trace and policy updates costly. Retrieval p
arXiv:2609.29553v1 Announce Type: cross Abstract: Automatic stress recognition from facial video provides a non-contact approach for affective monitoring. However, most existing video-based methods di
arXiv:2609.29875v1 Announce Type: new Abstract: Long horizon language model agents continually accumulate reasoning history, increasing context length and inference cost even after earlier decisions h
arXiv:2609.28832v1 Announce Type: new Abstract: Reconstruction-based unsupervised learning can fail in two opposing ways: a model may reconstruct anomalies too accurately or discard valid nominal vari
arXiv:2609.28475v1 Announce Type: new Abstract: Forecasting agents increasingly combine language-model reasoning, retrieval, ensembling, and calibration, but it remains unclear when each behavior shou
arXiv:2609.29964v1 Announce Type: cross Abstract: General-purpose vision-language models (VLMs) bring broad knowledge and spatial reasoning to robot manipulation, yet existing systems either use them
arXiv:2609.27690v1 Announce Type: new Abstract: Researchers in industry and academia use synthetic survey respondents powered by large language models as substitutes for human samples. These synthetic
arXiv:2609.28471v1 Announce Type: new Abstract: Our results show that contrastive learning outperforms a classification-based approach to authorship verification under the tested settings. We identify
arXiv:2609.27014v1 Announce Type: cross Abstract: Legal contracts are structurally complex documents in which contradictions may emerge across distant and interconnected provisions. Although large lan
arXiv:2609.27702v1 Announce Type: cross Abstract: A camera and an IMU are the minimal sensor setup for metric localization and dense mapping, yet classical visual--inertial filters must wait for paral
arXiv:2609.27150v1 Announce Type: new Abstract: Multi-agent debate (MAD) has emerged as a promising paradigm for improving the reasoning accuracy of large language models (LLMs) through iterative peer
Don't sleep on using Jev-as-a-Judge for agent evaluation. This is one of the most impressive Jev use cases I have found so far. Jev is a natural fit as a Judge, but it doesn't mean you use it everywhe
arXiv:2511.19486v3 Announce Type: replace-cross Abstract: Driven by recent advances in artificial intelligence, a growing literature has demonstrated the potential of using large language models (LLMs
arXiv:2609.28182v1 Announce Type: new Abstract: Coordinating large population of flexible grid-edge devices can alleviate the need for time-consuming and capital-intensive network upgrades, and AI-bas
arXiv:2609.27779v1 Announce Type: new Abstract: Class-guided 3D object generation is important for intelligent content creation, virtual environments, and digital asset design. Although 3D Gaussian Sp
arXiv:2609.27695v1 Announce Type: new Abstract: Perceiving objects in the environment is a fundamental capability of autonomous robots. In dark or low-light environments, external cameras often fail t
arXiv:2609.27758v1 Announce Type: cross Abstract: Safety alignment in large language models is trained primarily in English, and recent work reports that the underlying harmfulness representation surv
arXiv:2609.27068v1 Announce Type: new Abstract: Pre-trained robot policies always require finetuning to adapt to specific environments. Reinforcement Learning (RL) offers high performance potential be
I am looking to hire PhD students, post-docs, and ML researchers in our Paris office interested in collaborating on fundamental research in AI model safety, not safety rules, not AI policy, not post h
Hey r/Ollama, I've been working on Presentation Forge, an open-source presentation/report generator that supports Ollama for local inference. I originally made it because I'm a university student and
Impressive paper from Salesforce. It discusses the importance of good verifiers for RL environments. Only 35.8% of the environments in the cleanest public RL collection for terminal agents passed Sale
Enterprises are increasingly standardizing on Google Kubernetes Engine (GKE) to run their most critical and AI-driven workloads. From Cloud Storage FUSE for high-throughput data access to custom compu
arXiv:2609.28078v1 Announce Type: new Abstract: Segmentation-based multi-object tracking (MOT) with foundation video models such as SAM2 offers strong localization quality, yet remains fragile in crow
arXiv:2609.27225v1 Announce Type: cross Abstract: Probabilistic question-answering systems -- whether large language models (LLMs) themselves, retrieval-augmented generation (RAG), or trained multi-ho
arXiv:2609.28239v1 Announce Type: new Abstract: With the development of applications like autonomous driving, object detection has gained significant attention, while also highlighting critical vulner
arXiv:2609.27489v1 Announce Type: cross Abstract: This paper introduces Passing, an interactive audiovisual installation that generates an endless journey from a single continuous monorail-window reco
arXiv:2609.27987v1 Announce Type: new Abstract: Large language models (LLMs) have made substantial progress on medical question-answering, yet effective medical dialogue also requires learning to ask
arXiv:2609.28270v1 Announce Type: new Abstract: Weight-space post-training quantization (PTQ) must choose finite formats, granularities, quantizer families, transformations, and bits before the comple
arXiv:2609.27532v1 Announce Type: cross Abstract: Long-horizon agentic tasks require an agent to modify an environment through a sequence of tool calls, with success determined by the final state. The
arXiv:2609.28081v1 Announce Type: cross Abstract: Conventional image registration algorithms are robust to domain shifts and achieve low errors, but they are slow and computationally expensive. Deep-l
arXiv:2609.28263v1 Announce Type: new Abstract: The growth of large language model (LLM) inference and search services increases the scale of online linear programming problems, motivating computation
arXiv:2604.01173v2 Announce Type: replace-cross Abstract: Uncertainty quantification is essential when deploying learning-based control methods in safety-critical systems. This is commonly realized by
arXiv:2609.28006v1 Announce Type: new Abstract: Decoder-only Transformer language models cache keys and values (KV) to reuse past computation during generation. Sharing KV across layers saves storage