Knowledge catalogue
arXiv:2506.20904v2 Announce Type: replace Abstract: We study offline reinforcement learning in average-reward MDPs, which presents increased challenges from the perspectives of distribution shift and
arXiv:2604.19832v1 Announce Type: cross Abstract: In a global derivatives market with notional values in the hundreds of trillions of dollars, the accuracy and efficiency of pricing models are of fund
Our own team was trying to figure out how to get LiteParse working in the browser 😂 Shouldn't have doubted Claude. Claude knows best. LiteParse is really neat! It does a great job of extracting text f
Over the past month, some of you reported Claude Code's quality had slipped. We investigated, and published a post-mortem on the three issues we found. All are fixed in v2.1.116+ and we’ve reset usage
arXiv:2604.20423v1 Announce Type: new Abstract: The rapid iteration of autonomous driving algorithms has created a growing demand for high-fidelity, replayable, and diagnosable testing data. However,
arXiv:2604.20835v1 Announce Type: new Abstract: Modern language models demonstrate impressive coding capabilities in common programming languages (PLs), such as C++ and Python, but their performance i
ParseBench is now live on @Kaggle. The first document OCR benchmark built for AI agents — 2,000 enterprise pages, 167K+ test rules, 5 dimensions that actually break downstream agents. Benchmark your p
arXiv:2604.19784v1 Announce Type: cross Abstract: Recently, it has been found that frontier AI models can resist their own shutdown, a behavior known as self-preservation. We extend this concept to th
arXiv:2602.07044v2 Announce Type: replace-cross Abstract: Pipeline integrity is critical to industrial safety and environmental protection, with Magnetic Flux Leakage (MFL) detection being a primary n
arXiv:2603.21373v2 Announce Type: replace-cross Abstract: In-context learning (ICL) adapts large language models by conditioning on a small set of ICL examples, avoiding costly parameter updates. Amon
arXiv:2604.20834v1 Announce Type: new Abstract: Recent advances in Vision-Language-Action (VLA) models have opened new avenues for robot manipulation, yet existing methods exhibit limited efficiency a
Generative artificial intelligence security startup Portal26 Inc. today announced the launch of a new module designed to rein in runaway token consumption by autonomous AI agents, a problem the compan
arXiv:2604.19773v1 Announce Type: cross Abstract: The construction of CAD models has traditionally relied on labor-intensive manual operations and specialized expertise. Recent advances in large langu
arXiv:2604.19795v1 Announce Type: new Abstract: We introduce prism{} (extbf{P}robabilistic extbf{R}etrieval with extbf{I}nformation-extbf{S}tratified extbf{M}emory), an evolutionary memory substrate f
This post demonstrates a DFlash implementation integrated with llama-cpp, showcasing a speculative decoding setup that uses Qwen 3.6-27B as the main model with a smaller draft model (dflash-draft-q4_k
arXiv:2604.20706v1 Announce Type: cross Abstract: With the growing synergy between deep learning and quantum computing, Quantum Neural Networks (QNNs) have emerged as a promising paradigm by leveragin
arXiv:2602.07085v2 Announce Type: replace-cross Abstract: Financial markets are noisy and non-stationary, making alpha mining highly sensitive to noise in backtesting results and sudden market regime
arXiv:2604.20000v1 Announce Type: new Abstract: Automated wildlife monitoring from aerial imagery is vital for conservation but remains limited by two persistent challenges: the difficulty of detectin
arXiv:2602.09520v2 Announce Type: replace Abstract: The Rashomon set captures the collection of models that achieve near-identical empirical performance yet may differ substantially in their decision
arXiv:2508.07050v3 Announce Type: replace-cross Abstract: Large Language Model (LLM) based listwise ranking has shown superior performance in many passage ranking tasks. With the development of Large
arXiv:2604.20543v1 Announce Type: new Abstract: Referring detection refers to locate the target referred by natural languages, which has recently attracted growing research interests. However, existin
arXiv:2604.20775v1 Announce Type: new Abstract: Trajectory Inference (TI) seeks to recover latent dynamical processes from snapshot data, where only independent samples from time-indexed marginals are
arXiv:2604.20738v1 Announce Type: new Abstract: We introduce a benchmark dataset for question answering and translation in bilingual Latin and English settings, containing about 7,800 question-answer
arXiv:2604.20258v1 Announce Type: new Abstract: Instruction-based image editing (IIE) aims to modify images according to textual instructions while preserving irrelevant content. Despite recent advanc
arXiv:2602.08580v2 Announce Type: replace-cross Abstract: Automatic extraction of retinal vascular biomarkers from color fundus images (CFI) is crucial for large-scale studies of the retinal vasculatu
arXiv:2601.08558v2 Announce Type: replace Abstract: Incomplete point clouds captured by 3D sensors often result in the loss of both geometric and semantic information. Most existing point cloud comple
arXiv:2506.22598v3 Announce Type: replace Abstract: Agents based on Large Language Models (LLMs) have shown promise for performing sophisticated software engineering tasks autonomously. In addition, t
arXiv:2604.20623v1 Announce Type: cross Abstract: Traditional change detection identifies where changes occur, but does not explain what changed in natural language. Existing remote sensing change cap
arXiv:2604.20209v1 Announce Type: new Abstract: LLM self-play algorithms are notable in that, in principle, nothing bounds their learning: a Conjecturer model creates problems for a Solver, and both i
arXiv:2604.19907v1 Announce Type: new Abstract: Recent agentic frameworks for 3D scene synthesis have advanced realism and diversity by integrating heterogeneous generation and editing tools. These to
arXiv:2601.12910v3 Announce Type: replace-cross Abstract: Discrepancies between scientific papers and their code undermine reproducibility, a concern that grows as automated research agents scale scie
arXiv:2512.08730v2 Announce Type: replace Abstract: Most existing methods for training-free open-vocabulary semantic segmentation are based on CLIP. While these approaches have made progress, they oft
arXiv:2604.20598v1 Announce Type: cross Abstract: Modern retrieval-augmented generation (RAG) systems treat vector embeddings as static, context-free artifacts: an embedding has no notion of when it w
arXiv:2604.20413v1 Announce Type: new Abstract: Large language models perform well on many reasoning tasks, yet they often lack awareness of whether their current knowledge or reasoning state is compl
arXiv:2604.19777v1 Announce Type: cross Abstract: Large Language Models (LLMs) exhibit a well-documented positional bias when processing long input contexts: information in the middle of a context win
arXiv:2604.20128v1 Announce Type: new Abstract: Fusing a low resolution (LR) mosaiced hyperspectral image (HSI) with a high resolution (HR) panchromatic (PAN) image offers a promising avenue for video
Claude's Opus 4.7 model was experiencing issues when used within Claude Code, and Anthropic's team was actively investigating the problems with plans to provide updates as they continued the rollout.
arXiv:2604.19888v1 Announce Type: new Abstract: Driver gaze estimation is essential for understanding the driver's situational awareness of surrounding traffic. Existing gaze estimation models use dri
This article by Ethan Mollick likely discusses emerging capabilities and implications of GPT-5.5, OpenAI's next-generation language model, exploring how it represents advancement in AI technology and
arXiv:2604.19793v1 Announce Type: new Abstract: LLM agents must select tools from large API libraries and order them correctly. Existing methods use semantic similarity for both retrieval and ordering
arXiv:2604.20087v1 Announce Type: new Abstract: Skills have become the de facto way to enable LLM agents to perform complex real-world tasks with customized instructions, workflows, and tools, but how
arXiv:2509.15174v3 Announce Type: replace-cross Abstract: WARNING: This paper contains examples of offensive materials. To address the proliferation of toxic content on social media, we introduce SMAR
Written by: JP Glab, Tufail Ahmed, Josh Kelley, Muhammad Umair Introduction Google Threat Intelligence Group (GTIG) identified a multistage intrusion campaign by a newly tracked threat group, UNC6692,
So right now basically anyone with a 16GB VRAM card can go on @huggingface and download a model which BEATS Claude Sonnet 4.5, all running locally 🤯 LOOK AT THE WATER PARTICLES?? What are they doing i
arXiv:2604.19752v1 Announce Type: cross Abstract: Multi-agent AI systems exhibit emergent risks that no single agent produces in isolation. Existing safety frameworks rely on binary classifications of
Zijing Wu / Financial Times: Sources: DeepSeek is fundraising to keep its researchers, some of whom have left for rivals whose valuations have soared; it is targeting a $20B valuation — Chinese AI sta
arXiv:2604.19841v1 Announce Type: cross Abstract: Accurate forecasting of electric vehicle (EV) charging demand is critical for grid management and infrastructure planning. Yet the field continues to
arXiv:2604.20842v1 Announce Type: cross Abstract: Paralinguistic cues are essential for natural human-computer interaction, yet their evaluation in Large Audio-Language Models (LALMs) remains limited
arXiv:2604.19877v1 Announce Type: new Abstract: We release Super Apriel, a 15B-parameter supernet in which every decoder layer provides four trained mixer choices -- Full Attention (FA), Sliding Windo
arXiv:2604.20727v1 Announce Type: cross Abstract: Training large foundation models for agentic tasks is increasingly impractical due to the high computational costs, long iteration cycles, and rapid o
arXiv:2604.20319v1 Announce Type: new Abstract: Fine-grained spatiotemporal reasoning on surgical videos is critical, yet the capabilities of Multi-modal Large Language Models (MLLMs) in this domain r
arXiv:2409.07609v2 Announce Type: replace-cross Abstract: Deploying adversarially robust machine learning systems requires continuous trade-offs between robustness, cost, and latency. We present an au
arXiv:2505.07849v2 Announce Type: replace-cross Abstract: Software issue localization, the task of identifying the precise code locations (files, classes, or functions) relevant to a natural language
arXiv:2604.20179v1 Announce Type: cross Abstract: The rapidly evolving Node.js ecosystem currently includes millions of packages and is a critical part of modern software supply chains, making vulnera
arXiv:2604.20216v1 Announce Type: new Abstract: Many applications of LLM-based text regression require predicting a full conditional distribution rather than a single point value. We study distributio
Thanks @lennysan for a great conversation about how Claude Code maintains product velocity, how the product management role is shifting in the AI era, and the future of work! https://open.spotify.com/
That browser version of LiteParse is available here: https://simonw.github.io/liteparse/ Detailed notes on how I built it using Claude Code (running for an hour) on my blog: https://simonwillison.net/
arXiv:2604.20225v1 Announce Type: new Abstract: Evaluating the multilingual and multicultural capabilities of Large Language Models (LLMs) is essential for their global utility. However, current bench
arXiv:2603.29025v2 Announce Type: replace-cross Abstract: Large language models systematically fail when a salient surface cue conflicts with an unstated feasibility constraint. We study this through
arXiv:2511.03690v2 Announce Type: replace-cross Abstract: Agents are now used widely in the process of software development, but building production-ready software engineering agents is a complex task