model releases

I was going to say LangChain Labs is the most exciting thing we’ve announced recently, but with so many launches it’s hard to justify… but still incredibly thrilled to see this get started!! Checkout

arXiv:2605.12785v1 Announce Type: new Abstract: Hybrid machine learning combines physical knowledge with data-driven models to enhance interpretability and performance. In this context, Port-Hamiltoni

arXiv:2605.12967v1 Announce Type: new Abstract: The rapid advancement of generative AI has enabled the creation of highly realistic and diverse synthetic images, posing critical challenges for image p

arXiv:2605.12999v1 Announce Type: cross Abstract: Closed-loop brain-computer interfaces often require both a forecast of upcoming neural population activity and a readout of the animal's behavioral st

arXiv:2602.04923v2 Announce Type: replace Abstract: Neural operators have emerged as powerful surrogates for the solution of partial differential equations (PDEs), yet their ability to handle general,

arXiv:2605.13292v1 Announce Type: cross Abstract: Most existing medical dialogue systems operate in a single-turn question--answering paradigm or rely on template-based datasets, limiting conversation

arXiv:2605.13338v1 Announce Type: cross Abstract: Large Reasoning Models (LRMs) are increasingly integrated into systems requiring reliable multi-step inference, yet this growing dependence exposes ne

arXiv:2605.12765v1 Announce Type: new Abstract: Large Language Models memorize vast amounts of training data, raising concerns regarding privacy, copyright infringement, and safety. Machine unlearning

arXiv:2605.12768v1 Announce Type: cross Abstract: Open time-series forecasting (TSF) benchmarks cover retail, energy, weather, and traffic, but supply-chain logistics remains underserved. We introduce

arXiv:2605.13322v1 Announce Type: new Abstract: Kamon (family crests) are an important part of Japanese culture and a natural test case for compositional visual recognition: each crest combines a smal

arXiv:2605.13160v1 Announce Type: cross Abstract: Modern Bayesian optimization and adaptive sampling methods increasingly rely on nonlinear parametric models, yet theoretical guarantees for such model

Kimi K2.6 and DeepSeek V4 Pro are now GA on @FireworksAI_HQ on Foundry + PTU support in the US Data Zone—predictable performance, data residency, enterprise SLAs. Frontier open models. Azure controls.

Kimi K2.6 is now open-weight #1 on Finance Agent Benchmark V2. Can AI do the job of a financial analyst? We just released V2 of our Finance Agent Benchmark and tested the frontier models. The results

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