Knowledge catalogue
arXiv:2605.11491v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has become an effective paradigm for improving the reasoning ability of large language models. How
arXiv:2505.19770v5 Announce Type: replace-cross Abstract: We present a fine-grained theoretical analysis of the performance gap between two-stage reinforcement learning from human feedback~(RLHF) and
arXiv:2605.11059v1 Announce Type: cross Abstract: We study the large-depth limit of transformers trained with AdamW, by modelling the hidden-state dynamics as an interacting particle system (IPS) coup
arXiv:2605.11856v1 Announce Type: cross Abstract: Multimodal large language models are increasingly expected to perform thinking with images, yet existing visual latent reasoning methods still rely on
Ollama v0.23.4 is a release version of Ollama, a tool for running large language models locally. This patch release likely includes bug fixes, performance improvements, and refinements to existing fea
arXiv:2605.11864v1 Announce Type: cross Abstract: Listwise reranking is a key yet computationally expensive component in vision-centric retrieval and multimodal retrieval-augmented generation (M-RAG)
arXiv:2603.11383v2 Announce Type: replace Abstract: Teleoperation of low-cost robotic manipulators remains challenging due to the difficulty of retargeting human hand motion to robot joint commands. W
We built SmithDB: the database purpose built for agent observability workloads that now powers many parts of LangSmith. Agent observability presents a challenging data problem. Agent traces can contai
arXiv:2605.11654v1 Announce Type: new Abstract: Cross-view geo-localization (CVGL), which matches an oblique drone view to a geo-referenced satellite tile, has emerged as a key alternative for autonom
arXiv:2605.11559v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have become a key interface for visual reasoning and grounded question answering, yet they remain vulnerable to
When you want to move from single agent SQLite on something like QMD, PostgreSQL is a great choice for multi agent and production quality, but not as snappy. So we made it much more snappy with BM25 &
💡 Why did @togethercompute choose NVIDIA Blackwell to serve DeepSeek-V4? Because NVIDIA Blackwell is built for the bottlenecks that matter most in long-context inference: → KV-cache pressure during de
arXiv:2605.11521v1 Announce Type: new Abstract: Autonomous driving and intelligent transportation systems remain vulnerable under extreme weather. The U.S. Federal Highway Administration reports that
Nous Research has made Step 3.5 Flash, a faster AI model variant, available again on their portal at no cost for a 15-day period following popular demand after an initial 10-day availability window. T
arXiv:2605.08517v1 Announce Type: cross Abstract: We describe an approach for estimating the statistical risk of deep networks that contain a mix of learned and known operators. Building on the maxima
arXiv:2605.08436v1 Announce Type: cross Abstract: We introduce a meshfree exterior calculus (MEEC) for learning structure-preserving descriptions of physics on point clouds, and use it to build MEEC-N
arXiv:2512.06427v2 Announce Type: replace Abstract: Proper initialisation strategy is of primary importance to mitigate gradient explosion or vanishing when training neural networks. Yet, the impact o
arXiv:2605.09283v1 Announce Type: new Abstract: The evolution of Large Language Models (LLMs) and the software agents built on them (AI agents) marks a turning point in the transition from a human-cen
arXiv:2605.08150v1 Announce Type: new Abstract: We present a PyTorch package that compiles neural networks and their weights from Turing machine descriptions, producing models that exactly simulate th
arXiv:2512.17593v3 Announce Type: replace Abstract: In this paper we consider the limiting case of neural networks (NNs) architectures when the number of neurons in each hidden layer and the number of
arXiv:2605.09755v1 Announce Type: cross Abstract: The power method is one of the most fundamental tools for extracting top principal components from data through low-rank matrix approximation. Yet, wh
arXiv:2605.08408v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) provide a flexible framework for solving forward and inverse problems governed by partial differential equation
arXiv:2605.09902v1 Announce Type: new Abstract: Adversarial perturbations can mislead Multimodal Large Language Models (MLLMs) recognize a benign image as a specific target object, posing serious risk
arXiv:2605.09337v1 Announce Type: new Abstract: We propose FAR-SIGN (Fully Asynchronous Robust optimization via SIGNed directional projections) for adversary-resilient learning in parameter-server--wo
arXiv:2605.09186v1 Announce Type: new Abstract: Mixed-integer programming (MIP) research is both mathematically sophisticated and engineering-intensive: testing an algorithmic hypothesis within a bran
Vercel's AI Gateway production index is a monitoring tool that tracks the performance and reliability of AI services and models in production environments. It likely provides metrics on latency, uptim
arXiv:2605.09150v1 Announce Type: new Abstract: Poker is an imperfect information game that has served as a long-standing benchmark for decision-making under uncertainty. To maximize utility beyond th
arXiv:2605.10590v1 Announce Type: cross Abstract: Causal sensitivity analysis aims to provide bounds for causal effect estimates in the presence of unobserved confounding. However, existing methods fo
Rachel Metz / Bloomberg: Anthropic announces 12 Claude plugins for the legal sector, including a “commercial counsel” tool for reviewing vendor agreements and a bar exam study tool — Anthropic PBC is
arXiv:2605.10107v1 Announce Type: new Abstract: Assertion-based Verification (ABV) is essential for ensuring that hardware designs conform to their intended specifications. However, existing automated
arXiv:2605.08831v1 Announce Type: new Abstract: In flexible assembly systems, existing task planning methods require a time-consuming configuration process by multiple experts to establish a productio
arXiv:2605.10168v1 Announce Type: new Abstract: Document-based question answering (QA) increasingly includes abstract questions that require synthesizing scattered information from long documents or a
arXiv:2605.10871v1 Announce Type: cross Abstract: This work proposes Attractor-Vascular Coupling Theory (AVCT), a mathematical framework showing that cardiac attractor geometry encodes blood pressure
arXiv:2605.10169v1 Announce Type: new Abstract: Reachability games are two-player games played on a graph, where the objective of exttt{REACH} player is to reach the target set whereas the objective o
arXiv:2605.10845v1 Announce Type: cross Abstract: As global cross-lingual communication intensifies, language barriers in visually rich documents such as PDFs remain a practical bottleneck. Existing d
arXiv:2601.02950v3 Announce Type: replace Abstract: Current Large Language Model reasoning systems process queries independently, discarding valuable cross-instance signals such as shared reasoning pa
arXiv:2605.10655v1 Announce Type: new Abstract: Trellis-coded quantization sets the current 2-bit post-training frontier for LLMs (QTIP), but pushing below the PTQ ceiling requires quantization-aware
arXiv:2605.08421v1 Announce Type: new Abstract: Visual Document Retrieval (VDR) models mostly rely on late interaction architectures, in which documents are represented by a set of local patch embeddi
arXiv:2605.09268v1 Announce Type: cross Abstract: Users interacting with Large Language Models (LLMs) in a multi-turn conversation routinely refine their requests or pivot to new topics. LLMs, however
arXiv:2601.15686v2 Announce Type: replace Abstract: Model editing updates a pre-trained LLM with new facts or rules without retraining while preserving unrelated behavior. In real deployment, edits ar
arXiv:2605.09441v1 Announce Type: new Abstract: The pursuit of general-purpose embodied agents is hindered by fragmented evaluation protocols that isolate navigation skills and fixate on specific robo
arXiv:2605.09463v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated exceptional performance across diverse tasks. However, their deployment in long-context scenarios faces h
arXiv:2605.08271v1 Announce Type: cross Abstract: Understanding ultra-long videos such as egocentric recordings, live streams, or surveillance footage spanning days to weeks, remains a challenge. For
arXiv:2605.09096v1 Announce Type: new Abstract: Neural operators for time-dependent PDEs face a structural tension: spectral architectures (FNO and descendants) inherit exponential rollout-error growt
arXiv:2605.10661v1 Announce Type: cross Abstract: Vision Transformers (ViTs) are built by stacking independently parameterized blocks, but it remains unclear how much of this depth requires layer spec
arXiv:2605.09702v1 Announce Type: cross Abstract: Multi-judge evaluation is increasingly used to assess LLMs and reward models, and the prevailing heuristic is to curate: keep the most accurate judges
arXiv:2605.10448v1 Announce Type: new Abstract: Interactive agent benchmarks map an agent run to a binary outcome through outcome checks. When these checks rely on surface level signals or fail to cap
arXiv:2605.06638v2 Announce Type: replace Abstract: Reinforcement learning (RL) has been applied to improve large language model (LLM) reasoning, yet the systematic study of how training scales with t
arXiv:2605.08173v1 Announce Type: new Abstract: The generalization performance (GP) of deep learning-based arbitrary-scale image super-resolution (ASISR) methods is subject to limited training dataset
arXiv:2605.09223v1 Announce Type: new Abstract: Understanding long videos with multimodal large language models (MLLMs) requires selecting a small subset of informative frames under strict computation
arXiv:2605.10396v1 Announce Type: new Abstract: Neural networks have proved an effective means of learning control policies for autonomous systems, but these learned policies are difficult to understa
arXiv:2605.10586v1 Announce Type: new Abstract: Learning a physical model from video data that can comprehend physical laws and predict the future trajectories of objects is a formidable challenge in
arXiv:2605.09079v1 Announce Type: new Abstract: Despite surpassing human performance across mathematics, coding, and other knowledge-intensive tasks, large language models (LLMs) continue to struggle
arXiv:2605.10473v1 Announce Type: cross Abstract: We introduce a cavity-enhanced optical architecture for collective quantum processing in which logical qubits are encoded in the polarization subspace
arXiv:2605.08417v1 Announce Type: new Abstract: Designing model-free algorithms for distributionally robust reinforcement learning (DRRL) poses fundamental challenges. The robust Bellman operator is n
arXiv:2605.09676v1 Announce Type: cross Abstract: Spatio-temporal graph neural networks (STGNNs) are widely used for short-term forecasting in dynamic physical systems such as traffic and weather. How
arXiv:2603.05495v2 Announce Type: replace Abstract: To scale optimization and simulation, prior work has explored training machine-learning surrogates that map problem parameters to solutions inexpens
arXiv:2505.20654v2 Announce Type: replace-cross Abstract: Existing cyberbullying detection benchmarks were organized by the polarity of speech, such as 'offensive' and 'non-offensive', which were esse
Chroma1-HD is an 8.9B parameter text-to-image foundational model based on FLUX.1-schnell , ideal for finetuning on specific styles, concepts, or characters . The Reddit discussion likely covers techni
arXiv:2605.09168v1 Announce Type: new Abstract: A valid tool call is not necessarily a valid intervention. Tool-using language agents are guarded by schema validators, policy filters, provenance check