Search: “context”

arXiv:2605.11368v1 Announce Type: new Abstract: We study the application of recent Edit Flows for inference-time reward control for DNA sequence generation. Unlike most reward-guided DNA generation fr

arXiv:2509.22414v4 Announce Type: replace Abstract: Image restoration (IR) aims to recover images degraded by unknown mixtures while preserving semanticsconditions under which discriminative restorers

arXiv:2605.12449v1 Announce Type: new Abstract: While self-supervised pretraining has reduced vision systems' reliance on synthetic data, simulation remains an indispensable tool for closed-loop optim

arXiv:2605.11760v1 Announce Type: new Abstract: The Segment Anything Model 2 (SAM2) has emerged as a foundation model for universal segmentation. Owing to its generalizable visual representations, SAM

arXiv:2302.12039v2 Announce Type: replace Abstract: We summarize the current state of the field of NLP & Law with a specific focus on recent technical and substantive developments. To support our anal

Elon Musk posted on X about traveling to Beijing aboard Air Force One, indicating a trip to China's capital. The post suggests either an official government delegation or a significant business visit

arXiv:2605.11742v1 Announce Type: new Abstract: Online Continual Learning (OCL) aims to learn from endless nonext{-}stationary data streams, yet most existing methods assume a flat label space and ove

arXiv:2605.12419v1 Announce Type: new Abstract: Despite the rapid advancements in large language model (LLM) development, fine-tuning them for specific tasks often results in the catastrophic forgetti

At the Android Show yesterday, we introduced Googlebooks: a new category of premium laptops built with Gemini’s helpfulness at the core. Designed for Gemini Intelligence, Googlebooks will give persona

arXiv:2602.01418v2 Announce Type: replace Abstract: We propose Parabolic Position Encoding (PaPE), a parabola-based position encoding for vision modalities in attention-based architectures. Given a se

arXiv:2605.11730v1 Announce Type: new Abstract: Automated red-teaming for LLMs often discovers narrow attack slices, missing diverse real-world threats, and yielding insufficient data for safety fine-

arXiv:2605.11497v1 Announce Type: new Abstract: Zero-shot skeleton-based action recognition (ZSSAR) is typically treated as a skeleton-text alignment problem: encode joint-coordinate sequences, align

arXiv:2605.11363v1 Announce Type: cross Abstract: Presentation generation is moving beyond static slide creation toward end-to-end presentation video generation with research grounding, multimodal med

arXiv:2508.10036v2 Announce Type: replace Abstract: Large Language Models (LLMs) show remarkable potential for few-shot information extraction (IE), yet their performance is highly sensitive to the ch

arXiv:2605.11232v1 Announce Type: cross Abstract: Fraud detection and anti-money-laundering (AML) compliance are high-value domains for large language models (LLMs), but their serving requirements dif

arXiv:2605.11212v1 Announce Type: new Abstract: Computer-use agents~(CUAs) rely on visual observations of graphical user interfaces, where each screenshot is encoded into a large number of visual toke

arXiv:2605.12015v1 Announce Type: cross Abstract: Reusable skills are becoming a common interface for extending large language model agents, packaging procedural guidance with access to files, tools,

arXiv:2603.07388v2 Announce Type: replace Abstract: Explaining out-of-distribution generalization has been a central problem in epistemology since Goodman's 'grue' puzzle in 1946. Today it's a central

arXiv:2605.11483v1 Announce Type: new Abstract: While large language models excel at factual adaptation, their ability to internalize nuanced philosophical frameworks under severe data constraints rem

In the healthcare and life sciences industries, speed saves lives, but meeting regulatory requirements and other administrative burdens often pumps the brakes for manufacturers of software as a medica

The UK AISI found Mythos Preview is the first model to solve both their cyber ranges end-to-end. No model had ever solved the AISI’s “Cooling Tower” cyber range before. We're getting it to defenders a

arXiv:2605.12236v1 Announce Type: cross Abstract: Fine-tuning pre-trained robot policies with reinforcement learning (RL) often inherits the bottlenecks introduced by pre-training with behavioral clon

arXiv:2605.11974v1 Announce Type: new Abstract: Large Language Models (LLMs) suffer from order bias, where their performance is affected by the arrangement order of input elements. This unfairness lim

arXiv:2605.11993v1 Announce Type: new Abstract: Movie subtitle translation is inherently multimodal, yet text-only systems often miss visual cues needed to convey emotion, action, and social nuance, e

arXiv:2304.10891v2 Announce Type: replace-cross Abstract: Transformer-based models are becoming a central paradigm in autonomous driving because they can capture long-range spatial dependencies, multi

arXiv:2605.12220v1 Announce Type: new Abstract: Safe autonomous agents and mobile robots need fast real time 3D perception, especially for vulnerable road users (VRUs) such as pedestrians. We introduc

arXiv:2605.11911v1 Announce Type: new Abstract: Predictive Coding (PC) is an influential account of cortical learning. Much of recent work has focused on comparing PC to Backpropagation (BP) to find 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

We just shipped tons of new products to accelerate the full agent development lifecycle: https://www.langchain.com/blog TLDR: ✅ LangSmith Engine ✅ SmithDB ✅ Sandboxes ✅ Managed Deep Agents ✅ LLM Gatew

arXiv:2502.11981v3 Announce Type: replace Abstract: Decades of research in machine learning have given us powerful tools for making accurate predictions. But when used in social settings and on human

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:2605.08223v1 Announce Type: new Abstract: Federated techniques such as federated learning and federated analysis have emerged as a powerful paradigm for enabling multi-center research on sensiti

arXiv:2605.10643v1 Announce Type: new Abstract: Modern language models scale depth by stacking layers, each holding its own state - a per-layer KV cache in transformers, a per-layer matrix in Mamba, G

arXiv:2605.10566v1 Announce Type: cross Abstract: Probabilistic linear solvers (PLSs) return probability distributions that quantify uncertainty due to limited computation in the solution of linear sy

arXiv:2605.08647v1 Announce Type: cross Abstract: Multi-agent systems achieve state-of-the-art outcomes through peer collaboration. However, when an agent in the pipeline silently drops a constraint,

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

arXiv:2605.08480v1 Announce Type: new Abstract: Individuals with Alzheimer's disease (AD) and Alzheimer's disease-related dementia (ADRD) experience memory and thinking changes that impact their abili

arXiv:2605.09115v1 Announce Type: cross Abstract: Modern security environments generate fragmented signals across cloud resources, identities, configurations, and third-party security tools. Although

arXiv:2605.10328v1 Announce Type: new Abstract: A central challenge in large-scale decision-making under incomplete information is estimating reliable probabilities. Recent approaches leverage Large L

arXiv:2605.10876v1 Announce Type: cross Abstract: Recent advances in machine learning and large-scale biological data collections have revived the prospect of building a virtual cell, a computational

arXiv:2508.13813v2 Announce Type: replace-cross Abstract: As AI systems increasingly rely on training data, assessing dataset trustworthiness has become critical, particularly for properties like fair

arXiv:2509.08031v3 Announce Type: replace-cross Abstract: Large Audio Language Models (LALMs) are rapidly advancing, but evaluating them remains challenging due to inefficient and non-standardized too

arXiv:2605.08172v1 Announce Type: new Abstract: Anatomical mesh segmentation requires models that operate directly on irregular surface geometry while remaining robust to arbitrary patient pose and me

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:2605.09722v1 Announce Type: new Abstract: Obtaining an accurate short-term forecasting for heat demand is an essential part of operating district heating networks cost-efficient and reliable. He

arXiv:2605.10438v1 Announce Type: cross Abstract: Current 3D tokenizers largely treat representation as spatial compression: compact codes reconstruct surface geometry, but leave component ownership a