All entries

arXiv:2601.21972v4 Announce Type: replace Abstract: Recent work has explored optimizing LLM collaboration through Multi-Agent Reinforcement Learning (MARL). However, most MARL fine-tuning approaches r

arXiv:2605.03437v1 Announce Type: new Abstract: Detecting anomalies from 3D point clouds has received increasing attention in the field of computer vision, with some group-based or point-based methods

arXiv:2605.03373v1 Announce Type: new Abstract: Classical optimization theory establishes that zeroth-order (ZO) algorithms suffer from a dimension-dependent slowdown, with convergence rates typically

arXiv:2605.03462v1 Announce Type: new Abstract: A fundamental role in decoding human motor intent and enabling intuitive human-computer interaction is played by electromyography (EMG). However, its ge

arXiv:2605.03363v1 Announce Type: new Abstract: In this work, we propose a hybrid hierarchical control framework for reactive dexterous grasping that explicitly decouples high-level spatial intent fro

arXiv:2605.03059v1 Announce Type: new Abstract: Medical experts often manually segment images to obtain diagnostic statistics and discard the resulting annotations. We aim to train segmentation models

arXiv:2605.03413v1 Announce Type: new Abstract: What does it mean to understand the world? Contemporary world models often operationalize understanding as accurate future prediction in latent or obser

arXiv:2504.17816v3 Announce Type: replace Abstract: Subject-driven video generation (SDV-Gen) aims to produce videos of a specific subject by adapting a pretrained video model, enabling personalized a

arXiv:2605.01610v1 Announce Type: cross Abstract: AI systems have long been expected to interact with users, answering questions, generating content, and continuing (social) conversations. Agentic AI,

Let's consult the historical record to see what the Aztec society was up to when the Spanish conquered it. First, from Cortes: “They have a most horrid and abominable custom which truly ought to be pu

arXiv:2605.03620v1 Announce Type: cross Abstract: Syndrome-based neural decoding (SBND) has emerged as a promising deep learning approach for soft-decision decoding of high-rate, short-length codes. H

arXiv:2605.01293v1 Announce Type: new Abstract: Foundation model-driven agents often struggle with long-horizon planning due to the transient nature of purely prompting-based reasoning. While existing

arXiv:2601.19312v2 Announce Type: replace Abstract: The Schrodinger Bridge and Bass (SBB) formulation, which jointly controls drift and volatility, is an established extension of the classical Schrodi

Tim Harford compares large language models to tricksters, arguing that LLMs excel at generating plausible-sounding text without necessarily ensuring accuracy or truthfulness. The article likely explor

.@ListenLabs Co-Founder & CTO @florian_jue on the 2 types of engineers who build great agents: 1/ Those who know what LLMs can and can't do, and can feel when something's off 2/ Product engineers who

arXiv:2601.06445v2 Announce Type: replace Abstract: Computational narrative analysis aims to capture rhythm, tension, and emotional dynamics in literary texts. Existing large language models can gener

Simon Willison's live blog covers Anthropic's Code w/ Claude 2026 event, documenting the morning keynote sessions with real-time updates. The event featured announcements including updates to Claude m

arXiv:2605.01394v1 Announce Type: cross Abstract: Formal specification is essential for rigorous program verification, yet writing correct specifications remains costly and difficult to automate. Alth

LlamaIndex NYC takeover, 5/13 🗽 Our CEO Jerry Liu is in town. Two events, open to every NYC builder: 🛠️ FinParse Workshop — laptops out, hands-on with @jerryjliu0 → https://luma.com/updli8i6 🍕 AI Engi

arXiv:2605.03328v1 Announce Type: new Abstract: Additive manufacturing (AM) continues to transform modern manufacturing by enabling flexible, on-demand production of complex geometries across diverse

arXiv:2605.02455v1 Announce Type: cross Abstract: State-of-the-art Large Language Models (LLMs) excel in code generation at the function level. However, the output quality significantly declines when

arXiv:2605.02335v1 Announce Type: cross Abstract: Large Language Models (LLMs) have transformed agent-agent and human-agent interaction by enabling software, physical, and simulation agents to communi

arXiv:2505.16120v2 Announce Type: replace Abstract: The emergence of Large Language Models (LLMs) has reshaped agent systems. Unlike traditional rule-based agents with limited task scope, LLM-powered

arXiv:2605.03299v1 Announce Type: new Abstract: Cross-lingual topic modeling aims to discover shared semantic structures across languages, yet existing models depend on sparse bilingual resources and

arXiv:2605.01164v1 Announce Type: new Abstract: This position paper argues that LLMs should not yet be credited with decision explanation. This matters because recent work increasingly treats accurate

arXiv:2605.03386v1 Announce Type: new Abstract: Spatiotemporal forecasting in physical systems, such as large-scale traffic networks, requires modeling a dual dynamic: continuous macroscopic rhythms a

arXiv:2412.13235v4 Announce Type: replace Abstract: The logic-constrained shortest path problem (LCSPP) combines a one-to-one shortest path problem with satisfiability constraints imposed on the routi

arXiv:2605.03971v1 Announce Type: new Abstract: Large Language Models (LLMs) are prone to factual hallucinations, risking their reliability in real-world applications. Existing hallucination detectors

arXiv:2605.03736v1 Announce Type: cross Abstract: We consider a novel algorithm, for the completion of partially observed low-rank tensors, as a generalization of matrix completion. The proposed low-r

LTX 2.3 is a video generation tool that a content creator is using as their primary solution for video generation in a story-driven fantasy project. The post demonstrates practical application of LTX

arXiv:2605.03228v1 Announce Type: cross Abstract: As large language model (LLM)-powered agents are increasingly deployed to perform complex, real-world tasks, they face a growing class of attacks that

arXiv:2511.01680v3 Announce Type: replace-cross Abstract: Social scientists are increasingly turning to unstructured datasets to unlock new empirical insights, e.g., estimating descriptive statistics

arXiv:2605.03438v1 Announce Type: new Abstract: Pre-trained 3D point cloud foundation models (PFMs) have demonstrated strong transferability across diverse downstream tasks. However, full fine-tuning

Many have a view that China's government is authoritarian and driven by a desire to beat us. I think these are symptoms of far more interesting motivations. There is a lot of discourse about China. I

Many trials feel like Rashomon with different witnesses. The amazing thing about Musk-OpenAI is how much agreement there has been (at least so far) on the facts. The question is really whether what Op

arXiv:2605.01486v1 Announce Type: new Abstract: Legal consultation is a high-stakes, knowledge-intensive task that requires agents to identify relevant legal issues, retrieve authoritative support, an

arXiv:2605.03398v1 Announce Type: new Abstract: Video Temporal Grounding (VTG) faces a cross-modal semantic gap that often leads to background features being incorrectly aligned with the query, while

arXiv:2603.19294v2 Announce Type: replace-cross Abstract: While post-training has successfully improved large language models (LLMs) across a variety of domains, these gains heavily rely on human-labe

arXiv:2605.03858v1 Announce Type: new Abstract: Multi-constraint instruction following requires verifying whether a response satisfies multiple individual requirements, yet LLM judges are often assess

arXiv:2602.00933v2 Announce Type: replace-cross Abstract: The Model Context Protocol (MCP) is rapidly becoming the standard interface for Large Language Models (LLMs) to discover and invoke external t

arXiv:2601.06543v2 Announce Type: replace Abstract: Queueing simulation studies often require substantial manual effort to translate conceptual system descriptions into executable programs and to veri

arXiv:2604.05081v2 Announce Type: replace Abstract: We introduce MedGemma 1.5 4B, the latest model in the MedGemma collection. MedGemma 1.5 expands on MedGemma 1 by integrating additional capabilities

arXiv:2605.03343v1 Announce Type: new Abstract: Medical image super-resolution (MedSR) is essential for improving diagnostic precision across diverse imaging modalities such as MRI, CT, X-ray, Ultraso

arXiv:2605.03103v1 Announce Type: new Abstract: Semi-structured information extraction (IE) from OCR-derived clinical reports is crucial for efficiently reconstructing patients' longitudinal medical h

arXiv:2605.02199v1 Announce Type: new Abstract: Long-term LLM agents must compress streams of past interactions into persistent memory before future queries are known. Existing evaluations usually mea

arXiv:2605.02908v1 Announce Type: new Abstract: Understanding how textual embeddings contribute to memorization in text-to-image diffusion models is crucial for both interpretability and safety. This