Knowledge catalogue
arXiv:2605.20410v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in socially sensitive settings despite substantial documentation that they encode gender biases.
arXiv:2605.20297v1 Announce Type: new Abstract: Medical image segmentation faces a fundamental challenge in continual learning: data arrives sequentially from heterogeneous sources, yet effective cont
arXiv:2605.20197v1 Announce Type: new Abstract: Medical concept extraction from electronic health records underpins many downstream applications, yet remains challenging because medically meaningful c
📣Meet Qwen3.7-Max — our latest flagship, made for the Agent Era. A versatile foundation for agents that actually get things done: 🧑💻 Coding agent, end to end. Frontend prototypes, multi-file refactor
arXiv:2605.20833v1 Announce Type: new Abstract: Memory is a central capability for LLM agents operating across long-horizon tasks. Existing memory benchmarks predominantly evaluate retention of person
arXiv:2605.20723v1 Announce Type: new Abstract: Deploying large deep neural networks on memory-constrained mobile devices is a central challenge in edge ML. While compression, pruning, and quantizatio
arXiv:2605.20948v1 Announce Type: new Abstract: Scaling conditional memory offers a promising way to increase language-model capacity, but existing methods such as Engram learn large memory tables fro
🦔Microsoft canceled its internal Claude Code licenses this week after token-based billing made the cost untenable, even for a company with effectively infinite cloud resources. Uber's CTO sent an inte
arXiv:2605.21272v1 Announce Type: new Abstract: Training large text-to-image models requires high-quality, curated datasets with diverse content and detailed captions. Yet the cost and complexity of c
arXiv:2605.20729v1 Announce Type: new Abstract: Accurate evaluation of conversational retrieval is pivotal for advancing Retrieval-Augmented Generation (RAG) systems. However, existing conversational
arXiv:2602.24138v2 Announce Type: replace Abstract: Automated recognition of surgical phases and steps is a fundamental capability for intraoperative decision support, workflow automation, and skill a
arXiv:2605.21437v1 Announce Type: cross Abstract: Standard approaches to forecasting the weekly number of earthquakes on a spatial grid rely on the Poisson distribution with a single global dispersion
arXiv:2605.20525v1 Announce Type: cross Abstract: We present NeuroQA, a large-scale benchmark for visual question answering in 3D brain magnetic resonance imaging (MRI), with 56,953 QA pairs from 12,9
New inflection point in the accelerating growth of open-source models usage is coming 🦔Microsoft canceled its internal Claude Code licenses this week after token-based billing made the cost untenable,
arXiv:2605.21263v1 Announce Type: new Abstract: Firms increasingly rely on dynamic pricing to respond to evolving customer demand, yet in many applications they observe only the revenue generated by a
On Evals - getting messages on “ok so how do I actually start learning this?” there is no better way than by just doing so you can copy this to Claude Code and get started today <instructions> 1. Go l
arXiv:2605.20668v1 Announce Type: new Abstract: With the advancement of AI capabilities, AI reviewers are beginning to be deployed in scientific peer review, yet their capability and credibility remai
arXiv:2312.01386v2 Announce Type: replace Abstract: Gaussian process upper confidence bound (GP-UCB) is widely used for sequential optimization of expensive black-box functions. Although many upper bo
Open source 🤝 NVIDIA 👏 Congratulations to @cohere on Command A+ — a powerful new model optimized for NVIDIA Blackwell and trained using NVIDIA CUDA-X libraries. Proud to be a part of it! Learn more ⤵️
arXiv:2409.04777v4 Announce Type: replace Abstract: Large Language Models have driven significant AI advancements, yet their training is resource-intensive and highly sensitive to hyper-parameter sele
arXiv:2602.06862v2 Announce Type: replace Abstract: Adapting pre-trained vision models using parameter-efficient fine-tuning (PEFT) remains challenging, as it aims to achieve performance comparable to
arXiv:2605.21207v1 Announce Type: new Abstract: The rapid evolution of generative AI, from GANs to modern diffusion models, has resulted in increasingly subtle discriminative clues. These fine-grained
arXiv:2605.20873v1 Announce Type: cross Abstract: Planning is a fundamental capability for large language models (LLMs) because such complex tasks require models to coordinate goals, constraints, reso
arXiv:2605.20978v1 Announce Type: new Abstract: Graph Network Simulators (GNSs) have emerged as powerful surrogates for complex physics-based simulation, offering inherent differentiability and orders
arXiv:2605.21391v1 Announce Type: new Abstract: Metaphor requires a language model to resolve a token whose contextual meaning diverges from its basic literal sense. Understanding how transformer mode
arXiv:2605.20961v1 Announce Type: new Abstract: Existing 4D-driven video diffusion models primarily target plausible generation, but faithful 4D editing requires preserving source-observed regions whi
proof too complicated, Claude help ELI5 Today, we share a breakthrough on the planar unit distance problem, a famous open question first posed by Paul Erdős in 1946. For nearly 80 years, mathematician
arXiv:2605.20531v1 Announce Type: cross Abstract: Reliable verification of proofs remains a bottleneck for training and evaluating AI systems on hard mathematical reasoning. Fully formal proofs, in la
arXiv:2602.01273v4 Announce Type: replace Abstract: Recently, Diffusion Transformers (DiTs) have emerged in Real-World Image Super-Resolution (Real-ISR) to generate high-quality textures, yet their he
arXiv:2605.21486v1 Announce Type: new Abstract: Hyperparameter transfer allows extrapolating optimal optimization hyperparameters from small to large scales, making it critical for training large lang
arXiv:2510.00171v2 Announce Type: replace-cross Abstract: We investigate quantum reservoir computing (QRC) using a hybrid qubit-boson system described by the Jaynes-Cummings (JC) Hamiltonian and its d
arXiv:2512.09447v2 Announce Type: replace-cross Abstract: Structurally repetitive environments produce visually plausible but aliased LiDAR loop candidates that can destabilize pose-graph optimization
Vercel has announced the availability of Qwen 3.7 Max, a language model, through its Vercel AI Gateway platform. This integration allows developers to access and use Qwen 3.7 Max alongside other AI mo
arXiv:2605.20584v1 Announce Type: new Abstract: Mobile app marketplaces require developers to disclose standardized content rating descriptors (CRDs) to inform users about potentially sensitive or res
arXiv:2508.03578v2 Announce Type: replace Abstract: Radar-based human pose estimation enables privacy-preserving motion tracking for ambient intelligence, yet the noisy nature of radar sensing makes u
arXiv:2605.21195v1 Announce Type: new Abstract: Discrete autoregressive (AR) text-to-image (T2I) models pair a VQ tokenizer with an AR policy, and current post-training pipelines optimize only the pol
arXiv:2605.21112v1 Announce Type: new Abstract: 4D automotive radar is indispensable for autonomous driving due to its low cost and robustness, yet its point cloud sparsity challenges 3D object detect
arXiv:2605.20809v1 Announce Type: new Abstract: While Large Language Models (LLMs) demonstrate remarkable performance on zero-shot annotation tasks, they often struggle with the specialized convention
arXiv:2605.20506v1 Announce Type: cross Abstract: Humans learn social norms and behaviors from verbal feedback (e.g., a parent saying 'that was rude' or a friend explaining 'here's why that hurt'). Ye
arXiv:2605.20262v1 Announce Type: new Abstract: We study selective refusal editing as a three-way control problem: induce non-refusal on designated edit prompts while preserving benign behavior and ha
arXiv:2605.20737v1 Announce Type: new Abstract: Existing approaches for unsupervised 3D point cloud segmentation predominantly rely on a purely visual similarity-based learning-by-clustering paradigm,
arXiv:2605.20626v1 Announce Type: new Abstract: We present the University of Florida Gators submission to the AmericasNLP 2026 shared task on cultural image captioning for Indigenous languages. Our tw
arXiv:2605.21066v1 Announce Type: new Abstract: Recommender systems often rely on observational user--item interaction data, which is prone to selection bias due to users' selective interactions with
arXiv:2605.21429v1 Announce Type: cross Abstract: Tactile-based reinforcement learning (RL) is currently hindered by fragmented research and a focus on over-saturated orientation tasks. We introduce v
arXiv:2605.20868v1 Announce Type: new Abstract: KV cache quantization reduces the memory cost of long-context LLM inference, but introduces approximation error that is typically validated only empiric
arXiv:2605.21138v1 Announce Type: new Abstract: Smoothed implicit contact dynamics enables gradient-based planning and control for contact-rich tasks without predefined mode sequences. However, safety
arXiv:2605.20645v1 Announce Type: new Abstract: Foggy conditions are commonly encountered in real-world applications; however, existing action recognition approaches typically assume favorable weather
Seems GPT-5.2 reaches expert level in peer review: 45 scientists took 469 hours evaluating human & AI reviews on 82 papers. 'Surprisingly, current AI reviewers are competitive even with the top-rated
Self-Evolving in the Wild：Over the course of ~35 hours of continuous autonomous execution, the model performed 432 kernel evaluations across 1,158 tool calls. It wrote, compiled, profiled, and iterati
arXiv:2605.21341v1 Announce Type: cross Abstract: Functional bilevel methods estimate a lower-level function and plug it into a hypergradient, but this plug-in gradient can retain first-order bias whe
arXiv:2509.13648v3 Announce Type: replace Abstract: Generative recommendation plays a crucial role in personalized systems, predicting users' future interactions from their historical behavior sequenc
arXiv:2605.20510v1 Announce Type: new Abstract: Urban heat exposure is becoming an increasingly critical challenge due to the intensifying urban heat island effect. Fine-grained shade patterns, especi
arXiv:2605.20763v1 Announce Type: new Abstract: Rapid progress in aerodynamic shape optimization (ASO) has outpaced currently-available standardized evaluation frameworks. Fair comparison requires a u
arXiv:2602.06358v2 Announce Type: replace Abstract: We propose SHINE (Scalable Hyper In-context NEtwork), a scalable hypernetwork that can map diverse meaningful contexts into high-quality LoRA adapte
arXiv:2605.21147v1 Announce Type: cross Abstract: As the number of model parameters increases, parameter-efficient fine-tuning (PEFT) has become the go-to choice for tailoring pre-trained large langua
arXiv:2605.20189v1 Announce Type: cross Abstract: Despite the remarkable success of large language models (LLMs), they still face bottlenecks while deploying in dynamic, real-world settings with prima
arXiv:2605.05863v2 Announce Type: replace Abstract: Incorporating prior data into online reinforcement learning accelerates training but typically forces a difficult trade-off between high computation
arXiv:2605.21384v1 Announce Type: cross Abstract: As long-horizon coding agents produce more code than any developer can review, oversight collapses onto a single surface: the automated test suite. Re
arXiv:2605.20296v1 Announce Type: new Abstract: Fine-tuning a language model for a target task routinely degrades capabilities the training data never explicitly threatened. We study this phenomenon,
Spent Tuesday watching @Google I/O thinking about a question. If you build on @Android, what just changed for you? Short answer: your screen belongs to Gemini now. After this week, Google owns the AI,