Knowledge catalogue
arXiv:2605.15763v1 Announce Type: cross Abstract: Current state-of-the-art Quality Estimation (QE) in machine translation relies on massive, proprietary LLMs, raising data privacy concerns. We demonst
arXiv:2605.15848v1 Announce Type: cross Abstract: Conversational interfaces powered by large language models (LLMs) are widely used for ideation and analysis, yet their linear structure limits explora
arXiv:2605.15728v1 Announce Type: cross Abstract: Category-level 6D object pose estimation is typically formulated as a multi-category joint learning problem with fully shared model parameters. Howeve
arXiv:2605.15942v1 Announce Type: cross Abstract: Open-vocabulary segmentation models often struggle to generalize to unseen combinations of object categories and attributes, because fine-grained desc
arXiv:2511.19399v3 Announce Type: replace-cross Abstract: Deep research agents perform multi-step research to produce long-form, well-attributed answers. However, most open deep research agents are tr
arXiv:2605.15542v1 Announce Type: new Abstract: GUI agents powered by Multimodal Large Language Models (MLLMs) have demonstrated impressive capability in understanding and executing user instructions.
arXiv:2605.16223v1 Announce Type: cross Abstract: Generative video models are increasingly used in design animation tasks, yet no standardized evaluation framework exists for this domain. Unlike natur
Every time I ask my 10-year-old to use coding agents, he gets extremely disappointed. It turns out that all he wants is to build his own rocket simulator. No amount of context engineering helps. No mo
arXiv:2604.05966v2 Announce Type: replace Abstract: Financial reporting systems increasingly leverage Large Language Models (LLMs) to extract and summarize corporate disclosures. However, most existin
arXiv:2605.15492v1 Announce Type: cross Abstract: Generative models such as diffusion and flow matching have become dominant paradigms for visuomotor policy learning, yet their reliance on iterative d
arXiv:2605.15282v1 Announce Type: new Abstract: Literary translation requires balancing target-language fluency with faithfulness to the source. Recent large language models (LLMs) often produce fluen
arXiv:2312.05975v3 Announce Type: replace-cross Abstract: Explainability is a vital aspect of modern AI for real-world impact and usability. The main objective of this paper is to emphasise the need t
arXiv:2605.16026v1 Announce Type: cross Abstract: Compositional speech-to-speech translation (S2ST) systems built upon speech large language models (SpeechLLMs) have recently shown promising performan
arXiv:2605.15862v1 Announce Type: new Abstract: Adaptive biomechanical systems may show similar observable gait performance while differing in latent organization and longitudinal behavior. This study
arXiv:2605.15880v1 Announce Type: cross Abstract: Thermal infrared imaging is robust to illumination variations and smoke interference, making it important for all-weather perception. However, the lac
arXiv:2605.15491v1 Announce Type: cross Abstract: Layer pruning removes entire Transformer decoder blocks from large language models, but introduces a mismatch between the hidden state received by the
arXiv:2511.14482v2 Announce Type: replace-cross Abstract: Join ordering is the NP-hard problem of selecting the most efficient order in which to evaluate joins (conjunctive, binary operators) in a dat
arXiv:2605.15238v1 Announce Type: cross Abstract: Large language models are increasingly used for code generation, but many generated programs fail to compile, a prerequisite for further correctness c
arXiv:2605.16193v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to simulate human opinions and survey responses, but their ability to reproduce population responses
arXiv:2504.09544v3 Announce Type: replace-cross Abstract: Recent advances in self-supervised deep learning have improved our ability to quantify cellular morphological changes in high-throughput micro
arXiv:2602.04909v3 Announce Type: replace Abstract: Direct Preference Optimization (DPO) and related methods align large language models from pairwise preferences by regularizing updates against a fix
arXiv:2605.16143v1 Announce Type: new Abstract: Large language model based agents often fail in unfamiliar environments due to premature exploitation: a tendency to act on prior knowledge before acqui
'Moonlit Stroll by Grok Imagine' appears to be an AI-generated image created using xAI's Grok image generation model, shared via X (formerly Twitter). The post likely showcases Grok's capabilities in
arXiv:2512.04745v3 Announce Type: replace-cross Abstract: The ability to flexibly compose previously acquired skills to execute intelligent behaviors is a hallmark of natural intelligence. Such compos
arXiv:2605.15219v1 Announce Type: new Abstract: Can AI systems discover genuinely new knowledge through iterative self improvement, and if so, at what cost? We introduce the NOVA framework, which mode
arXiv:2605.15435v1 Announce Type: new Abstract: Standard deep-learning pipelines usually choose the network architecture before training and keep it fixed throughout optimization. In contrast, a model
arXiv:2603.05377v2 Announce Type: replace-cross Abstract: Open-world navigation requires robots to make decisions in complex everyday environments while adapting to flexible task requirements. Convent
arXiv:2605.15403v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models rely on balanced expert utilization to fully realize their scalability. However, existing load-balancing methods are lar
arXiv:2605.15298v1 Announce Type: cross Abstract: Vision-language-action models have advanced rapidly, but robot trajectories alone provide limited coverage for learning broad physical understanding.
arXiv:2605.15665v1 Announce Type: new Abstract: Deploying large language model (LLM)-driven conversational agents in enterprise settings requires prompts that are simultaneously correct at launch and
arXiv:2605.15529v1 Announce Type: cross Abstract: Process Reward Models (PRMs) provide step-level feedback for reasoning, but current PRMs usually output only a single reward score for each step. Down
In recent weeks, we pointed Mythos and other security-focused LLMs at live code across critical parts of our infrastructure. We share what we observed, the models’ strengths and weaknesses, and what t
arXiv:2605.15641v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as general planners in embodied intelligence, enabling high level coordination and low level task pla
arXiv:2511.09884v2 Announce Type: replace Abstract: Mission critical (MC) applications such as defense operations, energy management, cybersecurity, and aerospace control require reliable, determinist
arXiv:2605.15908v1 Announce Type: cross Abstract: Natural images are continuous, yet most generative models synthesize them on discrete grids, limiting resolution-flexible generation. Continuous neura
arXiv:2605.16052v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have significantly enhanced automated legal reasoning. Yet, it remains unclear whether their performance
arXiv:2605.15976v1 Announce Type: cross Abstract: Production machine translation relies overwhelmingly on encoder-decoder Seq2Seq models, yet reinforcement learning approaches to MT fine-tuning have l
arXiv:2605.15425v1 Announce Type: cross Abstract: Agentic coding systems increasingly use large language models (LLMs) for software engineering tasks such as debugging, root cause analysis, and code r
arXiv:2605.16067v1 Announce Type: new Abstract: We propose a variational quantum classifier operating on high dimensional deep representations via amplitude encoding, stabilized by a learnable classic
arXiv:2601.06366v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are transforming enterprise workflows but introduce security and ethics challenges when employees inadvertently s
arXiv:2604.02268v2 Announce Type: replace Abstract: Agent skills, structured packages of procedural knowledge and executable resources that agents dynamically load at inference time, have become a rel
arXiv:2605.15915v1 Announce Type: cross Abstract: AI emotional companions face a safety-rapport paradox: restrictive safeguards can damage supportive alliance, while permissive systems risk user harm.
arXiv:2605.15433v1 Announce Type: new Abstract: Electroencephalograph (EEG) timeseries signals are characterized by significant noise and coarse spatial resolution, which complicates the classificatio
arXiv:2605.15881v1 Announce Type: cross Abstract: The modeling and simulation of infinite-dimensional Hamiltonian systems are central problems in mathematical physics and engineering, however they pos
arXiv:2605.15207v1 Announce Type: new Abstract: Multi-agent LLM systems have shown promise for complex reasoning, yet recent evaluations reveal they often underperform single-model baselines. We ident
arXiv:2605.15613v1 Announce Type: new Abstract: Through an analysis of sequences generated by open-weight large language models (LLMs), we demonstrate that LLMs are heavily biased toward English. Whil
arXiv:2512.00778v2 Announce Type: replace Abstract: Preference optimization (PO) is indispensable for large language models (LLMs), with methods such as direct preference optimization (DPO) and proxim
arXiv:2510.06062v2 Announce Type: replace Abstract: Reinforcement learning (RL) has shown great promise in large language models (LLMs) post-training, which typically rely on token-level clipping to m
arXiv:2605.15505v1 Announce Type: new Abstract: In enterprise operations, the context required for an AI agent task is scattered across systems of record, static information stores, and communication
b9197 is a build release of llama.cpp , an open-source C/C++ implementation that enables efficient large language model inference on various hardware platforms. The release includes cross-platform bin
ComfyUI's credit system was added to support Partner Nodes that use closed-source AI models, though ComfyUI remains fully open-source and free for local users. A unified Comfy Credits system was intro
The AMD Ryzen AI Max+ 395 'Strix Halo' APU outperforms the NVIDIA RTX 5080 by up to 3x in AI benchmarks, particularly for language models, with 128GB of accessible VRAM compared to the RTX 5080's 16GB
WebWright is a Chrome browser extension that enables AI agents to automate web tasks directly within the browser, leveraging local models like those available through Ollama. The announcement on r/oll
Transformer architecture is a neural network design that uses self-attention mechanisms to process data in parallel rather than sequentially, making it highly efficient for processing large amounts of
Gary Marcus critiques AI companies for training large language models on copyrighted books and other proprietary content without permission or compensation to authors. He argues that these companies e
pleased to be in this and encourage everyone to read: Awesome new theme issue of Philosophical Transactions: ‘World models in natural and artificial intelligence’ Thank you @adamsafron! https://royals
arXiv:2605.14489v1 Announce Type: new Abstract: Building black-box models for dynamical systems from data is a challenging problem in machine learning, especially when asymptotic stability guarantees
arXiv:2603.27517v3 Announce Type: replace-cross Abstract: AI agent frameworks connecting large language model (LLM) reasoning to host execution surfaces -- shell, filesystem, containers, and messaging
arXiv:2512.11855v2 Announce Type: replace-cross Abstract: Enforcing exact symmetry in machine learning models often yields significant gains in scientific applications, serving as a powerful inductive
arXiv:2605.13907v1 Announce Type: cross Abstract: Reinforcement learning (RL) for large language models (LLMs) is dominated by the cost of rollout generation, which has motivated the use of low-precis