Knowledge catalogue
arXiv:2605.01403v1 Announce Type: new Abstract: Multi-label node classification (MLNC) has recently been addressed by increasingly complex label-aware designs that explicitly model node-label interact
arXiv:2605.02623v1 Announce Type: new Abstract: Video Moment Retrieval (VMR) aims to localize temporal segments in videos that correspond to a natural language query, but typically assumes only a sing
arXiv:2605.01831v1 Announce Type: new Abstract: Reinforcement Learning from Human Feedback has become the standard paradigm for language model alignment, where reward models directly determine alignme
arXiv:2605.02370v1 Announce Type: new Abstract: This paper presents a novel model predictive control (MPC) approach for autonomous pick-and-place between moving platforms with a hook-equipped aerial m
arXiv:2605.01339v1 Announce Type: new Abstract: Learning-based approaches to verifying unknown Markov decision processes (MDPs) often employ uncertain MDPs. These models use, for example, confidence i
arXiv:2605.00966v1 Announce Type: new Abstract: Hierarchical Gaussian Filtering (HGF) networks allow for efficient updating of posterior distributions (beliefs) about hidden states of an agent's envir
arXiv:2605.00916v1 Announce Type: new Abstract: Reliable segmentation of multiphase pore-scale X-ray images of rocks is necessary to quantify fluid saturation, connectivity, and interfacial geometry.
arXiv:2605.01429v1 Announce Type: cross Abstract: Libraries of Low-Rank Adaptation (LoRA) adapters are becoming a practical by-product of parameter-efficient adaptation. Once such adapters accumulate,
arXiv:2510.13768v2 Announce Type: replace Abstract: We study the problem of training self-supervised foundation models for functional MRI. Our main contributions are: (1) we introduce a new model fami
arXiv:2605.01489v1 Announce Type: cross Abstract: Frontier scientific reasoning is rapidly emerging as a key foundation for advancing AI agents in automated scientific discovery. Deep research agents
See you all soon! We've got some fun announcements ahead. I'll also be doing a workshop on 'how we Claude Code' with some workflows I'm excited to share. Don't worry if you're not there, everything wi
arXiv:2605.02757v1 Announce Type: new Abstract: Vision-language-action (VLA) models typically rely on large-scale real-world videos, whereas simulated data, despite being inexpensive and highly parall
arXiv:2603.27259v2 Announce Type: replace Abstract: Long video understanding (LVU) remains a core challenge in multimodal learning. Although recent vision-language models (VLMs) have made notable prog
arXiv:2605.01327v1 Announce Type: cross Abstract: Existing reinforcement learning approaches for Large Language Models typically perform policy optimization at the granularity of individual tokens or
arXiv:2605.01823v1 Announce Type: new Abstract: Recently, Reinforcement Learning from Verifiable Rewards (RLVR) has been established as a highly effective technique for augmenting the math reasoning s
arXiv:2303.10971v2 Announce Type: replace Abstract: The matching of 3D shapes has been extensively studied for shapes represented as surface meshes, as well as for shapes represented as point clouds.
arXiv:2605.02601v1 Announce Type: new Abstract: We present our shared task on evaluating the adaptability of LLMs and NLP systems across multiple languages and cultures. The task data consist of an ex
arXiv:2605.01191v1 Announce Type: new Abstract: Vision-language-action (VLA) models have advanced the field of embodied manipulation by harnessing broad world knowledge and strong generalization. Howe
arXiv:2605.01496v1 Announce Type: new Abstract: This report presents the results and findings of the first edition of the Short-Films 20K (SF20K) Competition, held in conjunction with the SLoMO Worksh
arXiv:2605.02475v1 Announce Type: cross Abstract: Stories hold a reader's attention because they have causes, secrets, and consequences. Shadow-Loom is an experimental open-source framework that turns
arXiv:2605.02105v1 Announce Type: cross Abstract: Pretraining optimizers are tuned to produce the strongest possible base model, on the assumption that a stronger starting point yields a stronger mode
arXiv:2605.00519v2 Announce Type: cross Abstract: The operational landscape of local Large Language Model (LLM) inference has shifted from lightweight models to datacenter-class weights exceeding 70B
arXiv:2605.00382v2 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly deployed to generate code for human-centered applications where demographic fairness is critical. Howeve
Some things never change. If you don’t understand this one, you don’t understand what’s happening AI. Marcus, 1998: neural nets have trouble generalizing far beyond the data. Marcus, 2001, 2012, 2019,
arXiv:2605.00835v1 Announce Type: new Abstract: Choosing between classical and Bayesian sparse regression methods involves a real trade-off: penalized estimators like Lasso run in milliseconds but giv
arXiv:2605.02152v1 Announce Type: new Abstract: Diffusion-based image editing offers strong semantic controllability, but remains computationally expensive due to iterative high-resolution denoising o
arXiv:2605.02684v1 Announce Type: new Abstract: Spectral-based machine learning models have been increasingly deployed in chemometrics and spectroscopy, where predictive accuracy is as important as ex
arXiv:2605.01466v1 Announce Type: new Abstract: Although multi-modal learning has advanced point cloud completion, the theoretical mechanisms remain unclear. Recent works attribute success to the conn
arXiv:2601.17616v2 Announce Type: replace Abstract: Continual learning in Large Language Models (LLMs) is hindered by the plasticity-stability dilemma, where acquiring new capabilities often leads to
arXiv:2605.01905v1 Announce Type: cross Abstract: For the speaker-controlled spoken language identification task proposed in the TidyLang Challenge 2026, this paper proposes a language identification
arXiv:2605.00974v1 Announce Type: cross Abstract: LLMs are increasingly equipped with safety alignment mechanisms, yet recent studies demonstrate that they remain vulnerable to jailbreaking attacks th
arXiv:2601.08510v3 Announce Type: replace Abstract: Movie screenplays are rich long-form narratives that interleave complex character relationships, temporally ordered events, and dialogue-driven inte
arXiv:2605.02860v1 Announce Type: cross Abstract: Cross-language code clone detection (X-CCD) is challenging because semantically equivalent programs written in different languages often share little
arXiv:2605.02404v1 Announce Type: new Abstract: Model quantization has become essential for efficient large language model deployment, yet existing approaches involve clear trade-offs: methods such as
arXiv:2605.01653v1 Announce Type: new Abstract: We introduce SteeringDiffusion, a bottlenecked activation-level control interface for diffusion models that exposes a smooth, monotonic, and runtime-adj
arXiv:2602.08245v2 Announce Type: replace Abstract: Diffusion policies have recently emerged as a powerful paradigm for visuomotor control in robotic manipulation due to their ability to model the dis
arXiv:2504.17401v2 Announce Type: replace Abstract: Stereo disparity estimation is crucial for obtaining depth information in robot-assisted minimally invasive surgery (RAMIS). While current deep lear
arXiv:2605.02568v1 Announce Type: new Abstract: DeepSeek-V3.2 and V4 introduce Compressed Sparse Attention (CSA): a lightning indexer (a learned scoring projection over compressed keys) scores them, t
arXiv:2605.01939v1 Announce Type: new Abstract: Static benchmarks for LLMs are increasingly compromised by contamination and overfitting especially on knowledge intensive reasoning tasks While recent
arXiv:2605.00924v1 Announce Type: new Abstract: AI-generated content (AIGC) detectors are increasingly deployed in high-stakes settings such as academic integrity screening, yet their reliability rest
arXiv:2605.02209v1 Announce Type: cross Abstract: Evaluating large language models across many benchmarks is expensive, yet many benchmarks are highly correlated. We formalize the selection of a small
Subquadratic, a company developing a novel generative artificial intelligence model, launched today with 29 million in seed funding. The new large language model, dubbed SubQ, uses what the company ca
arXiv:2605.01911v1 Announce Type: new Abstract: Purpose: Vision-language models (VLMs) have shown promising performance in surgical visual question answering (VQA). However, existing surgical VQA data
arXiv:2508.15658v5 Announce Type: replace Abstract: The rapid growth of academic literature makes the manual creation of scientific surveys increasingly infeasible. While large language models show pr
arXiv:2605.01060v1 Announce Type: cross Abstract: We present SURGE, a streaming GPU encoding system deployed in production to generate embeddings for over 800 million texts across 40,000 logical parti
arXiv:2605.01931v1 Announce Type: cross Abstract: Channel estimation is crucial in 5G communication networks for optimizing transmission parameters and ensuring reliable, high-speed communication. How
arXiv:2603.00191v2 Announce Type: replace-cross Abstract: Continual Learning (CL) requires models to sequentially adapt to new tasks without forgetting old knowledge. Recently, Low-Rank Adaptation (Lo
arXiv:2605.01717v1 Announce Type: new Abstract: Conversational Aspect-based Sentiment Quadruple Analysis (DiaASQ) needs to capture the complex interrelationships in multiple rounds of dialogues. Exist
arXiv:2605.01077v1 Announce Type: new Abstract: Brazil's Unified Health System (SUS) relies on official clinical guidelines that define diagnostic criteria, treatments, dosages, and monitoring procedu
arXiv:2504.20605v2 Announce Type: replace Abstract: Moral stories are a time-tested vehicle for transmitting values, yet modern NLP lacks a large, structured corpus that couples coherent narratives wi
arXiv:2605.02672v1 Announce Type: cross Abstract: The 2026 ACII Dyadic Conversations (ACII-DaiKon) Workshop & Challenge introduces a benchmark for modeling interpersonal affect and social dynamics in
arXiv:2605.01771v1 Announce Type: new Abstract: An auditor instructs an AI assistant: 'open each file individually using the Read tool -- no scripts, no agents.' The AI replies 'Yes' -- then issues a
arXiv:2605.02398v1 Announce Type: cross Abstract: As frontier AI models are deployed in high-stakes decision pipelines, their ability to maintain metacognitive stability -- knowing what they do not kn
arXiv:2510.01020v2 Announce Type: replace Abstract: We study sequential testing for a binary disease outcome when risk follows an unknown logistic model. At each round, the decision maker may either p
arXiv:2604.04465v2 Announce Type: replace Abstract: This paper identifies a structural limitation in current multimodal AI architectures that is topological rather than parametric. Contrastive alignme
There’s a bunch of conflicting stances I don’t fully understand in the debate of Proprietary RL’d vs Open Harness, Model intelligence, and Agent Labs building harnesses for bespoke tasks Not all of th
arXiv:2504.15077v5 Announce Type: replace Abstract: Large Language Models (LLMs) can translate natural language into SQL, but small models struggle with multi-table and complex queries in Zero-Shot Le
arXiv:2601.05300v2 Announce Type: replace-cross Abstract: Reasoning-oriented language models typically expose explicit reasoning as a long, front-loaded chain of 'thinking' tokens before the main outp
arXiv:2605.02767v1 Announce Type: new Abstract: Diffusion models have recently demonstrated strong performance for image restoration tasks, including super-resolution. However, their large model size
arXiv:2510.15545v4 Announce Type: replace Abstract: Accelerating the inference of large language models (LLMs) has been a critical challenge in generative AI. Speculative decoding (SD) substantially i