model releases

arXiv:2603.02175v4 Announce Type: replace-cross Abstract: Instruction-based video editing has witnessed rapid progress, yet current methods often struggle with precise visual control, as natural langu

LangChain 在 Interrupt 大会上发布了底层数据库 SmithDB 和自动化排障引擎 LangSmith Engine。 Agent 运行会产生海量 trace（执行轨迹），把旧数据库撑到了瓶颈。新底座 SmithDB 放弃了本地磁盘，全面转向对象存储，将核心查询速度拉高了 15 倍。 底座换新后，LangSmith Engine 顺势接管了查 Bug 的体力活。它在后台持续监控生

arXiv:2603.03295v2 Announce Type: replace-cross Abstract: Whether in agentic workflows, social studies, or chat settings, large language models (LLMs) are increasingly being asked to replace humans in

arXiv:2605.13045v1 Announce Type: new Abstract: The existing methods for evaluating the medical knowledge of Large Language Models (LLMs) are largely based on atemporal examination-style benchmarks, w

arXiv:2605.13137v1 Announce Type: cross Abstract: Proving theorems in Lean 4 often requires identifying a scattered set of library lemmas whose joint use enables a concise proof -- a task we call glob

arXiv:2506.11274v2 Announce Type: replace-cross Abstract: Test-time scaling has emerged as an effective approach for improving language model performance by utilizing additional compute at inference t

arXiv:2605.13751v1 Announce Type: new Abstract: Establishing trustworthy safety assurance for autonomous driving systems (ADSs) requires evidence that failures arise from avoidable system deficiencies

arXiv:2505.15616v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have achieved significant advances in integrating visual and linguistic information, yet their ability to r

arXiv:2605.12789v1 Announce Type: new Abstract: Large language-vision models (LVLMs) such as CLIP, Flamingo, and BLIP have revolutionized AI by enabling understanding across textual and visual modalit

arXiv:2605.13424v1 Announce Type: new Abstract: We propose last-mile fine-tuning, or Lift, a pipeline in which a pre-trained large language model extracts an initial table from unstructured clipboard

Like any AI dev not employed by a closed lab, we share the ambition that at least 10x more should be capable of training frontier models in 2026. And like we all know, some 10x leaps can't survive a c

arXiv:2605.13412v1 Announce Type: cross Abstract: Off-the-shelf large language models (LLMs) are increasingly used to automate text annotation, yet their effectiveness remains underexplored for underr

NVIDIA AI has released an official getting started guide for Hermes on DGX Spark, providing new users with foundational resources and instructions for deploying or working with Hermes on NVIDIA's DGX

arXiv:2507.00029v2 Announce Type: replace-cross Abstract: Recent attempts to combine low-rank adaptation (LoRA) with mixture-of-experts (MoE) for multi-task adaptation of Large Language Models (LLMs)

arXiv:2605.12752v1 Announce Type: new Abstract: LoRA is widely adopted for continual fine-tuning of Large Language Models due to its parameter efficiency, modularity across tasks, and compatibility wi

Nikkei Asia: LY Corp launches a bid with Bain Capital to buy Kakaku.com, which operates restaurant review and booking site Tabelog, for 4B, challenging EQT's 3.75B offer — TOKYO — The operator of the

arXiv:2605.13511v1 Announce Type: cross Abstract: In-context learning (ICL) adapts large language models (LLMs) to new tasks by conditioning on demonstrations in the prompt without parameter updates.

arXiv:2601.21731v2 Announce Type: replace Abstract: Prior-Data Fitted Networks (PFNs) enable amortized Bayesian inference in a single forward pass, yet their internal representations remain opaque. It

arXiv:2605.13688v1 Announce Type: new Abstract: Medical segmentation foundation models such as SAM and MedSAM provide strong prompt-driven segmentation, but their image encoders are still too large fo

arXiv:2603.24649v2 Announce Type: replace Abstract: Medical imaging benchmarks often evaluate VLMs on pre-selected 2D images, slices, crops, or patches, making evaluation closer to visual recognition.

Meet Kimi Web Bridge - Kimi's browser extension. Agent can now interact with websites like a human: search, scroll, click, type and complete tasks. Supports Kimi Code CLI, Claude Code, Cursor, Codex,

DeepSeek maintains the highest efficiency in terms of active parameters relative to total model size, outperforming competitors in the ratio of parameters actually used during inference versus total t

Microsoft first started opening up access to Claude Code in December, inviting thousands of its own developers to use Anthropic's AI coding tool daily. It was part of an effort to get project managers

arXiv:2605.12624v1 Announce Type: cross Abstract: Autonomous driving has progressed from modular pipelines toward end-to-end unification, and Vision-Language-Action (VLA) models are a natural extensio

arXiv:2605.13551v1 Announce Type: new Abstract: Neural Posterior Estimation (NPE) enables rapid parameter inference for complex simulators with intractable likelihoods. NPE trains an inference network

arXiv:2605.12703v1 Announce Type: cross Abstract: We introduce MMCL-Bench, a benchmark for multimodal context learning: learning task-local rules, procedures, and empirical patterns from visual or mix

arXiv:2512.12634v3 Announce Type: replace Abstract: Mobile GUI Agents, AI agents capable of interacting with mobile applications on behalf of users, have the potential to transform human computer inte

arXiv:2507.10797v2 Announce Type: replace Abstract: This paper introduces the framework of multi-armed sampling, which serves as the sampling counterpart to the optimization problem of multi-armed ban

arXiv:2605.13190v1 Announce Type: cross Abstract: Improving the inference efficiency of autoregressive transformers typically means reducing FLOPs per token, usually through approximations that degrad

arXiv:2605.13829v1 Announce Type: cross Abstract: We introduce Negation Neglect, where finetuning LLMs on documents that flag a claim as false makes them believe the claim is true. For example, models

arXiv:2605.13072v1 Announce Type: cross Abstract: The quantum approximate optimization algorithm (QAOA) holds promise for combinatorial optimization but is constrained by limited qubits. While divide-

arXiv:2605.13817v1 Announce Type: cross Abstract: Natural-language software requirements are often ambiguous, inconsistent, and underspecified; in safety-critical domains, these defects propagate into

arXiv:2605.12678v1 Announce Type: new Abstract: Geospatial foundation models (GFMs) have been proposed as generalizable backbones for disaster response, land-cover mapping, food-security monitoring, a

arXiv:2605.13815v1 Announce Type: new Abstract: LiDAR scene generation is increasingly important for scalable simulation and synthetic data creation, especially under diverse sensing conditions that a

Zac Hall / 9to5Mac: OpenAI adds remote access to Codex in the ChatGPT mobile app, letting users control Codex sessions running on a connected computer directly from a phone — OpenAI has released a new

OpenAI is going to let users access Codex, its desktop AI tool that can write code and use apps on your computer, from the ChatGPT app on your phone. Following the surge in popularity for Anthropic's

arXiv:2605.12825v1 Announce Type: cross Abstract: We introduce Orthrus, a simple and efficient dual-architecture framework that unifies the exact generation fidelity of autoregressive Large Language M

arXiv:2605.13473v1 Announce Type: new Abstract: Linear attention and state-space models offer constant-memory alternatives to softmax attention, but often struggle with in-context associative recall.

arXiv:2605.13297v1 Announce Type: new Abstract: Periodic crystals repeatedly instantiate similar local coordination motifs across translated cells and chemically related structures, but current equiva

arXiv:2605.13169v1 Announce Type: cross Abstract: Multimodal large laboratory models (MLLMs) still struggle with spatial understanding under the dominant perspective-image paradigm, which inherits the

arXiv:2605.13807v1 Announce Type: cross Abstract: Neural-network quantum states have emerged as a powerful variational framework for quantum many-body systems, with recent progress often driven by mas

arXiv:2605.13487v1 Announce Type: new Abstract: Flow Matching is a powerful framework for learning transport maps between probability distributions. Yet its standard single-parameter formulation is no

arXiv:2605.13670v1 Announce Type: new Abstract: Accurate and efficient battery detection is increasingly important for applications in electronic waste recycling, industrial quality control, and autom

arXiv:2605.12525v1 Announce Type: cross Abstract: Current emotion analysis in social media is predominantly author-centric, failing to capture the subjective nature of emotional responses across diver

arXiv:2605.12850v1 Announce Type: cross Abstract: Fine-tuning large language models on narrow data with harmful content produces broadly misaligned behavior on unrelated prompts, a phenomenon known as

arXiv:2601.09636v2 Announce Type: replace Abstract: While GUI agents have shown strong performance under explicit and completion instructions, real-world deployment requires aligning with users' more