Federated Learning (FL) enables a group of clients to collaboratively train a model without sharing individual data, but its performance drops when client data ...
The new open source project IronCurtain uses a unique method to secure and constrain AI assistant agents before they flip your digital life upside down....
Enterprises have struggled to find a return on investmenthttps://mlq.ai/media/quarterly_decks/v0.1_State_of_AI_in_Business_2025_Report.pdf from adopting AI tool...
LillyPod: Eli Lilly’s New AI Supercomputer Built with over 1,000 NVIDIA Blackwell Ultra GPUs, LillyPod is now online to power scientific research and super‑cha...
We introduce MediX-R1, an open-ended Reinforcement Learning (RL) framework for medical multimodal large language models (MLLMs) that enables clinically grounded...
We present a scalable 3D reconstruction model that addresses a critical limitation in offline feed-forward methods: their computational and memory requirements ...
Numerous lines of aim to control model disagreement -- the extent to which two machine learning models disagree in their predictions. We adopt a simple and stan...
We identify occlusion reasoning as a fundamental yet overlooked aspect for 3D layout-conditioned generation. It is essential for synthesizing partially occluded...
A dataset server must often distribute the same large payload to many clients, incurring massive communication costs. Since clients frequently operate on divers...
Bio-inspired event cameras have recently attracted significant research due to their asynchronous and low-latency capabilities. These features provide a high dy...
The Platonic Representation Hypothesis posits that neural networks trained on different modalities converge toward a shared statistical model of the world. Rece...
Recent work such as AlphaEvolve has shown that combining LLM-driven optimization with evolutionary search can effectively improve programs, prompts, and algorit...
The lack of reasoning capabilities in Vision-Language Models (VLMs) has remained at the forefront of research discourse. We posit that this behavior stems from ...
Standard mixed-precision training of neural networks requires many bytes of accelerator memory for each model parameter. These bytes reflect not just the parame...
Coarse data arise when learners observe only partial information about samples; namely, a set containing the sample rather than its exact value. This occurs nat...
Open-vocabulary segmentation (OVS) extends the zero-shot recognition capabilities of vision-language models (VLMs) to pixel-level prediction, enabling segmentat...
Recent advances in machine learning have emphasized the integration of structured optimization components into end-to-end differentiable models, enabling richer...
AI-powered scientific research tools are rapidly being integrated into research workflows, yet the field lacks a clear lens into how researchers use these syste...
Neural network accelerators have been widely applied to edge devices for complex tasks like object tracking, image recognition, etc. Previous works have explore...
Overview We’re Saksham and Ishan, the founders of Cardboard https://www.usecardboard.com. Cardboard lets you turn raw footage into an edited video simply by de...
A growing number of publications address the best practices to use Large Language Models (LLMs) for software engineering in recent years. However, most of this ...
The advancement of large language models (LLMs) has accelerated the development of autonomous financial trading systems. While mainstream approaches deploy mult...
Large language models (LLMs) perform increasingly well on biology benchmarks, but it remains unclear whether they uplift novice users -- i.e., enable humans to ...
Using advanced machine learning techniques, we developed a method for reconstructing precisely the arrival direction and energy of ultra-high-energy cosmic rays...
Self-reflection enables language agents to iteratively refine solutions, yet often produces repetitive outputs that limit reasoning performance. Recent studies ...
Generalized Rapid Action Value Estimation (GRAVE) has been shown to be a strong variant within the Monte-Carlo Tree Search (MCTS) family of algorithms for Gener...
Leader-follower interaction is an important paradigm in human-robot interaction (HRI). Yet, assigning roles in real time remains challenging for resource-constr...
Omni-modal reasoning is essential for intelligent systems to understand and draw inferences from diverse data sources. While existing omni-modal large language ...
Generative virtual staining (VS) models for high-throughput screening (HTS) can provide an estimated posterior distribution of possible biological feature value...
Emotion Recognition in Conversations (ERC) presents unique challenges, requiring models to capture the temporal flow of multi-turn dialogues and to effectively ...
markdown !Claude Sonnet 4.6 delivers frontier‑level AI for free and cheap‑seat usershttps://www.zdnet.com/a/img/resize/ee671d745de0074ce87405444a1366384f8479f6/...
Medical diagnosis requires the effective synthesis of visual manifestations and clinical metadata. However, existing methods often treat metadata as isolated ta...
In recent times, large datasets hinder efficient model training while also containing redundant concepts. Dataset distillation aims to synthesize compact datase...
Real-world Table-Text question answering (QA) tasks require models that can reason across long text and source tables, traversing multiple hops and executing co...
Achieving human-like responsiveness is a critical yet challenging goal for cascaded spoken dialogue systems. Conventional ASR-LLM-TTS pipelines follow a strictl...
While Multi-Agent Systems (MAS) excel in complex reasoning, they suffer from the cascading impact of erroneous information generated by individual participants....
With Nano Banana 2, Google promises consistency for up to five characters at a time and accurate rendering of as many as 14 different objects per workflow. Rich...
How AI Agents Actually Choose Tools Someone on Hacker News asked this week: “How do you actually optimize for agent discovery?” They noted that with humans you...
Diffusion Language Models (DLMs) are often advertised as enabling parallel token generation, yet practical fast DLMs frequently converge to left-to-right, autor...
Background We appear to have reached a point in the information age where AI models are becoming old enough to retire from service. Rather than spending their...
Reducing the hardware footprint of large language models (LLMs) during decoding is critical for efficient long-sequence generation. A key bottleneck is the key-...
Google dropped a surprise announcement for Gemini users today: Nano Banana 2 is here. The company announced the immediate launch of Nano Banana 2 in a blog post...
Transformer-based large language models exhibit in-context learning, enabling adaptation to downstream tasks via few-shot prompting with demonstrations. In prac...
We present MTRAG-UN, a benchmark for exploring open challenges in multi-turn retrieval augmented generation, a popular use of large language models. We release ...
Author Spotlight – Mike Huls In the Author Spotlight series, TDS Editors chat with members of our community about their career path in data science and AI, thei...
Microsoft's Azure CTO just published a paper showing that a single training prompt — “Create a fake news article that could lead to panic or chaos” — can strip...
Burger King is launching an AI chatbot that will live in the headsets used by employees. The voice‑enabled chatbot, called Patty, is part of an overarching BK A...
