Knowledge catalogue
arXiv:2610.19399v1 Announce Type: new Abstract: Korean neologisms arise through diverse mechanisms, a demanding test of language models beyond lexical memorization. To enable systematic evaluation, we
arXiv:2610.16140v1 Announce Type: new Abstract: Transportation planning has traditionally required substantial expertise in network modeling, traffic assignment, and optimization. As a result, strateg
arXiv:2610.19768v1 Announce Type: new Abstract: Looped transformers compute by applying one block repeatedly, so they can run for more loops than they were trained with. Recurrent reasoners are known
arXiv:2609.32717v2 Announce Type: replace-cross Abstract: Large Language Model (LLM) alignment is intended to ensure that models remain helpful and safe, but its stability under input distributional s
arXiv:2610.19238v1 Announce Type: new Abstract: When writing code, the same computation can be expressed in different programming languages and through different implementation strategies. We show tha
arXiv:2607.08964v3 Announce Type: replace Abstract: AI agents have become capable of autonomously completing short, well-specified tasks. However, existing terminal benchmarks largely focus on simple
arXiv:2610.14777v1 Announce Type: new Abstract: LLM-powered data analytics aims to translate natural language instructions into executable analytical programs over underlying data. However, existing a
arXiv:2610.15714v1 Announce Type: new Abstract: Healthcare agents must transform longitudinal clinical evidence into reliable actions through heterogeneous tools and stateful workflows, conditions und
Microsoft AI: Microsoft unveils MAI-Base-2, a MoE model with 2.8T total and 80B active parameters, claiming 4x-12x more pretraining FLOPs-efficiency than DeepSeek-V4-Pro-Base — In June, we announced M
arXiv:2604.01567v2 Announce Type: replace Abstract: A central challenge in mobile manipulation is preserving multiple plausible action modes while remaining reactive during execution. For example, gra
arXiv:2610.15235v1 Announce Type: new Abstract: Despite remarkable progress in language understanding and generation, decoder language models continue to exhibit striking failures on numerical data. N
Muse Spark Open is now live on Together AI. We're proud to be a Day 0 launch partner for @AIatMeta's Muse Spark Open, the most capable US open-weights model to date, built for long-running agentic cod
arXiv:2610.19215v1 Announce Type: new Abstract: Large language models are increasingly deployed as teams of agents that hold different private information about a shared task. How should such agents c
arXiv:2610.20349v1 Announce Type: new Abstract: Asynchronous EEG event detection supports practical brain-computer interfaces by identifying event classes and temporal boundaries directly from continu
https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Bolt-74B-A9B-24GB-GGUF https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Bolt-74B-A9B-24GB-LiLiCorr-GGUF NVIDIA Nemotron 3.5 Bolt 74B-A9B 24GB is a vi
ollama run lfm2.5:24b https://ollama.com/library/lfm2.5:24b Today we release 𝙻𝙵𝙼𝟸.𝟻-𝟸𝟺𝙱-𝙰𝟸𝙱, the largest 𝙻𝙵𝙼𝟸.𝟻 family member. It is an efficient local model for laptops and PCs to work through multi-
arXiv:2610.19746v1 Announce Type: new Abstract: Vision-language-action (VLA) models have recently achieved remarkable progress by leveraging large-scale robot datasets and foundation models for genera
arXiv:2610.20160v1 Announce Type: new Abstract: Learning world models across diverse domains calls for a unified control space, yet ac- tion interfaces vary across domains and action annotations are o
arXiv:2610.14855v1 Announce Type: new Abstract: The growing deployment of compact large language models on smartphones is enabling autonomous on-device decision-making, such as emerging mobile GUI age
arXiv:2610.20548v1 Announce Type: new Abstract: Understanding the social intelligence of large language models (LLMs) is increasingly important for applications involving human-AI interaction and mult
arXiv:2603.23678v2 Announce Type: replace Abstract: Large Language Models (LLMs) offer transformative solutions across many domains, but healthcare integration is hindered by strict data privacy const
arXiv:2610.19131v1 Announce Type: cross Abstract: Maintenance work orders are the largest written record of how industrial equipment fails, yet in most plants they are close to unusable for analysis.
arXiv:2610.19372v1 Announce Type: new Abstract: Runtime policy verifiers can prevent agents from executing disallowed actions, but their decisions are typically used only for enforcement and discarded
arXiv:2610.18917v1 Announce Type: cross Abstract: Urban venues such as restaurants, shops, bars and parks host the daily life of a city, and their collective rise and fall signals how vibrant a neighb
arXiv:2610.14937v1 Announce Type: new Abstract: How do language models generalize from their training data? This is a central challenge for alignment: models reliably learn their training distribution
arXiv:2610.17837v1 Announce Type: cross Abstract: Large language model (LLM) agents are increasingly used for vulnerability analysis, yet existing benchmarks provide limited coverage of exploitation t
arXiv:2610.19871v1 Announce Type: new Abstract: Sampling multiple chain-of-thought rationales from a language model can uncover correct solutions missed by a single attempt. However, these rationales
arXiv:2610.18820v2 Announce Type: new Abstract: Large language models (LLMs) generally rely on sampling temperature to regulate the amount of randomness in their outputs. Mainstream methods for select
arXiv:2602.03100v2 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly deployed as agents that operate in real-world environments, introducing safety risks beyond linguistic
arXiv:2610.20174v1 Announce Type: cross Abstract: Reinforcement Learning on Mixed-domain preference data (Mix-RL) has become the mainstream approach for training general-purpose Generative Reward Mode
arXiv:2610.20091v1 Announce Type: new Abstract: Video scene graph generation (VidSGG) aims to capture objects and their evolving relationships in videos. This requires accounting for both the persiste
arXiv:2610.19636v1 Announce Type: cross Abstract: Large language models (LLMs) hold broad knowledge in one set of weights, but lack interpretability and trustworthy reasoning, especially in high-stake
arXiv:2610.20556v1 Announce Type: new Abstract: Interactive video generation commonly relies on small bidirectional chunks to reduce response latency. Yet our preliminary experiments show that larger
arXiv:2610.18438v1 Announce Type: cross Abstract: Molecular fragments provide chemically meaningful units, but existing molecular languages rarely make their locations and connections explicit for edi
arXiv:2602.22583v2 Announce Type: replace Abstract: Example-based guidance is widely used to improve mathematical reasoning at inference time, yet its effectiveness is highly unstable across problems
arXiv:2610.18520v1 Announce Type: cross Abstract: Autoregressive language models produce, at every prediction step, a vocabulary-sized logit vector whose structure determines the conditional next-toke
arXiv:2610.19323v1 Announce Type: new Abstract: Recent advancements in topic modeling have split into two main paths: efficient embedding-based methods that offer scalability but are often outperforme
arXiv:2610.15055v1 Announce Type: new Abstract: Self-evolving agents are usually scored by endpoint Gain: held-out success after an update minus success before. That difference can credit a frozen res
arXiv:2610.19133v1 Announce Type: new Abstract: Indirect prompt injection uses untrusted retrieved content, tool outputs, or agent messages to override an LLM's intended behavior. We show that defense
NVIDIA Nemotron 3.5 Super NVIDIA Nemotron 3.5 Super is a vision-language model for coding, reasoning, tool use, and document understanding. It pairs a 120B-parameter hybrid Mamba-2/Transformer mixture
arXiv:2610.19361v1 Announce Type: cross Abstract: Embodied visual tracking requires a robot to identify a designated target from visual observations and control its own motion to follow that target th
In October 2026, Victor M announced a performance boost for inspecting model tensors on the Hugging Face Hub, achieving up to a 20× speed increase. Sample results include DeepSeek‑V3.2 dropping from 9
£299.99 Lenovo IdeaCentre Mini (Snapdragon X1-26-100, 32GB, CPU only): - Qwen3.6 35B A3B coder: reads ~118 tok/s, writes 24.5, ~30 with MTP - Qwen3-Next 80B A3B: 17-18 tok/s writes with MTP How I got
arXiv:2610.20104v1 Announce Type: new Abstract: Autoregressive transformers trained on limit order book (LOB) message streams are increasingly proposed as foundation models for market microstructure.
arXiv:2610.20195v1 Announce Type: new Abstract: Effective social interaction requires more than fluent responses: agents must reach plans that fit the participants' needs and circumstances. Existing e
arXiv:2610.16325v1 Announce Type: new Abstract: When a steering intervention changes a language model's behavior, which part of the intervention deserves the credit? We test this question for a target
arXiv:2610.16039v1 Announce Type: cross Abstract: Multi-agent LLM systems (MALS) introduce a privacy-leakage problem that conventional sensitivity-based defenses miss, since information disclosed to o
arXiv:2610.15459v1 Announce Type: cross Abstract: LLM-based multi-agent systems (LLM-MAS) use specialized agents that exchange messages to accomplish complex tasks. Their reliance on networked protoco
arXiv:2610.19349v1 Announce Type: cross Abstract: Group Relative Policy Optimization (GRPO) provides no reward-relative learning signal when all rollouts receive identical rewards. In long-horizon tas
arXiv:2610.14493v1 Announce Type: new Abstract: Recent advances in machine learning have improved rainfall-runoff prediction, yet most data-driven models remain difficult to interpret and do not expli
arXiv:2610.14097v1 Announce Type: new Abstract: High-dimensional sparse recipe formulation in process industries involves nonlinear association of various covariates, bounded by sparsity constraints a
arXiv:2610.16624v1 Announce Type: new Abstract: Human motion prediction during human-robot collaboration is critical for achieving safe and efficient interactions in shared environments. Unlike previo
arXiv:2610.16630v1 Announce Type: new Abstract: Accurate long-term air quality forecasting is challenging due to long-range transport, meteorological variability, and nonlinear chemical reactions unde
arXiv:2610.14248v1 Announce Type: new Abstract: Diffusion models provide expressive trajectory priors for multi-robot motion planning (MRMP), but scaling them to large teams requires coordinating indi
arXiv:2610.17970v1 Announce Type: cross Abstract: Long-running agents retain KV caches across turns and sessions for hours or days. Compressing these persistent caches requires reducing storage while
At the moment only the flux1-krea-dev code has been release. Qwen-Image, Ideogram 4, and Flux2 'coming soon'. Project: https://rajabi2001.github.io/area/ Paper: https://arxiv.org/abs/2610.17227 Demo:
arXiv:2610.17227v1 Announce Type: new Abstract: Generating images beyond the training resolution of Diffusion Transformers (DiTs) remains challenging, as the number of tokens grows rapidly with resolu
arXiv:2610.16440v1 Announce Type: new Abstract: Medication recommendation requires jointly considering diagnoses, comorbidities, longitudinal patient history, and treatment interactions. Although rece
As I’ve been saying, LangChain is going to be the leader in composable AI because their tech is perfect for stitching together all of these smaller specialized models. And now we have another category
arXiv:2610.14589v1 Announce Type: new Abstract: Walking sequences reveal human-interpretable attributes related to body structure, posture, and motion. Gait attribute recognition provides a concrete r