Knowledge catalogue
arXiv:2608.26149v1 Announce Type: new Abstract: Multi-table learning remains a major challenge in machine learning for healthcare and other complex information systems. Relational data combine several
arXiv:2608.26171v1 Announce Type: cross Abstract: Multi-stage LLM hiring pipelines (resume improvement, interview question generation, answer feedback) can fabricate credentials, inflate qualifiers, a
arXiv:2608.26879v1 Announce Type: new Abstract: Fusing multiple modalities is expected to improve model performance. However, on the MultiHuSE dataset, early, late, and symmetric attention fusion ofte
arXiv:2608.27286v1 Announce Type: new Abstract: Inferring molecular structures from multimodal spectroscopic measurements requires integrating complementary yet highly heterogeneous signals. However,
arXiv:2608.26317v1 Announce Type: cross Abstract: Frontier language models are increasingly marketed as omni systems that can perceive and respond across modalities. Existing evaluation frameworks, ho
VideoCardz.com: Modders get an experimental version of Nvidia's DLSS 5 Neural Rendering library running in over a dozen games after it leaked in NBA 2K27's early access build — DLSS 5 mod spreads to C
arXiv:2503.18856v3 Announce Type: replace Abstract: An important objective in computational biology is the efficient integration of multi-omics data. The task of integration comes with challenges: mul
arXiv:2602.04731v2 Announce Type: replace Abstract: Adapting general-purpose LLMs into domain-specialized dense retrievers typically requires large-scale training on mixed-domain data. We show that me
arXiv:2608.26344v1 Announce Type: new Abstract: We previously reported a ModernBERT encoder trained from scratch for Turkish (MoganBERT-TR) and a single-vector embedding model built on top of it (Moga
arXiv:2608.26283v1 Announce Type: cross Abstract: Extracting a shared set of unknown, not directly measurable quantities from multiple, heterogeneous datasets is a common challenge across scientific d
arXiv:2608.26529v1 Announce Type: new Abstract: In this paper, we explore multi-expert Conformal Risk Control (CRC) algorithms for pairwise LLM-as-a-Judge evaluation in open-ended dialogue. Our core i
arXiv:2608.26806v1 Announce Type: new Abstract: With the growing demand for processing multiple image sequences in real-world applications, various visual token pruning methods have emerged to mitigat
arXiv:2608.27039v1 Announce Type: cross Abstract: Accurately forecasting the movement of people in complex scenes requires reasoning over the past and present state of the entire environment. In this
arXiv:2608.26535v1 Announce Type: new Abstract: Audio-video generation is rapidly moving from prompt-driven synthesis toward multimodal conditioning, where text, images, audio, and video can jointly s
arXiv:2511.12631v3 Announce Type: replace-cross Abstract: While significant progress has been achieved in multimodal facial generation using semantic masks and textual descriptions, conventional featu
arXiv:2608.26288v1 Announce Type: new Abstract: Muon has emerged as a strong optimizer for the matrix-valued parameters in large language model pretraining, approximately orthogonalizing its momentum
arXiv:2608.26161v1 Announce Type: cross Abstract: Although Large Language Models (LLMs) demonstrate remarkable capabilities in reasoning and decision-making, high-fidelity probabilistic sampling remai
arXiv:2608.27004v1 Announce Type: new Abstract: Reliable evaluation of vision-language models (VLMs) and medical vision-language models (Medical-VLMs) requires calibrated confidence, particularly unde
arXiv:2608.27266v1 Announce Type: new Abstract: Efficiently improving autonomous agents across diverse tasks is central to accelerating recursive self-improvement (RSI) in agentic AI, with prompt opti
arXiv:2608.26124v1 Announce Type: new Abstract: Pricing automation in large-scale tourism is challenging because travel orders are highly unstructured, while pricing policies are complex, rapidly evol
arXiv:2608.26436v1 Announce Type: new Abstract: Neonatal mortality risk prediction from bedside monitoring data remains challenging due to extreme class imbalance, heterogeneous clinical risk factors,
arXiv:2608.26504v1 Announce Type: new Abstract: Neural surface reconstruction has emerged as a powerful paradigm for recovering high-quality 3D surfaces from multi-view images. However, recovering acc
arXiv:2607.15682v2 Announce Type: replace Abstract: Sampling from an unnormalized Boltzmann density requires proposals that move probability mass globally while retaining enough path-probability infor
arXiv:2608.26729v1 Announce Type: new Abstract: In recent years, transductive knowledge graph embedding models have been applied to tasks such as link prediction and query answering. Although knowledg
arXiv:2608.26764v1 Announce Type: cross Abstract: Machine learning offers a possible route to data-driven real-space renormalization when the relevant observables are nonlocal and difficult to prescri
arXiv:2608.26329v1 Announce Type: new Abstract: While tool-augmented Large Language Models have significantly improved multi-step reasoning in quantitative STEM tasks, a critical residual failure mode
arXiv:2608.26222v1 Announce Type: cross Abstract: Safety evaluation is critical for assessing whether aligned Large Language Models (LLMs) remain robust against jailbreak attacks. Existing automated t
arXiv:2607.02317v2 Announce Type: replace Abstract: The human brain processes dynamic visual input through hierarchically organized, functionally specialized regions. While recent in silico brain enco
Built the latest and I'm getting as much as 220 tokens per second and averaging in the 170s, I can't get over it. If anyone on here is on that project, fuckkkin' chapeau man, really incredible job. I
arXiv:2603.29353v3 Announce Type: replace Abstract: We introduce Nomad, a system for autonomous data exploration and insight discovery. Given a corpus of documents, databases, or other data sources, u
arXiv:2607.10591v2 Announce Type: replace Abstract: Non-binary bottom-up constituency parsing commonly uses arity-specific reductions such as (extsc{Reduce-}X#k), which jointly specify the mother labe
arXiv:2608.27340v1 Announce Type: new Abstract: Steering interventions targeting eval-awareness, a model's recognition that it is being tested, are increasingly used in safety evaluation pipelines, wh
arXiv:2608.26596v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are increasingly capable scientific assistants, yet they remain far from fully autonomous research. This transi
Now live (and free) at Marcus on AI: takeways on the OpenAI / Hugging Face attack, coauthored with @ZackKorman, focusing not so much on what the AI did as on what OpenAI should have done. https://gary
Obligatory plug for static embeddings. Are you using static embeddings in your projects? Would love to hear how people are leveraging them, whether for retrieval and beyond. Static embeddings offer un
arXiv:2608.27044v1 Announce Type: new Abstract: Multimodal representation learning has been shifting from traditional two-tower architectures to large language model (LLM)-based embedders due to their
arXiv:2608.26292v1 Announce Type: cross Abstract: Every memory-based knowledge editor in the SERAC lineage depends on a scope decision: given a query, does a stored edit apply? We report that current
arXiv:2608.26797v1 Announce Type: new Abstract: The rapid improvement of LLMs has made distinguishing AI-generated text from human writing a pressing problem. This challenge is further amplified by pa
arXiv:2608.26789v1 Announce Type: new Abstract: Accurate steering sensing and LiDAR-to-vehicle extrinsics are crucial for reliable path tracking in warehouse mobile robots (WMRs); miscalibration often
Proof is in the method honestly. Closed model labs need to constantly reinvent the wheel to keep lead. Open source has a bunch of independent labs practically working somewhat together. Eventually whe
OpenAI's own research says 80% of US GDP could be automated by agents today. So why isn't it? @swyx joined me on Navigators to break down what's actually holding back the adoption of agents (and it's
Ora runs agents on live websites and traces every step. When a signup, integration, or payment stalls, teams see which step, what the agent tried, and what to change. The whole platform is built on Ve
arXiv:2608.26866v1 Announce Type: new Abstract: Many multimodal tasks depend on how visual elements are ordered and composed, not only on recognizing them in isolation. Internet memes are a compact ca
A few days ago I posted asking what people considered the best local model for an 8 GB VRAM GPU. At the time, my personal sweet spot was Qwen3.6-35B-A3B, for agentic coding with Pi.dev. Well… Thanks t
arXiv:2601.20650v3 Announce Type: replace Abstract: Vast-horizon, repetitive workflows are common in daily routines, e.g., processing expense reports from a stack of receipts, organising a collection
Patrick Skinner tweets that the U.S. government is “broken” and urges citizens to reject and denounce what he calls “garbage” and its supporters. He emphasizes collective action as necessary to avoid
arXiv:2608.27137v1 Announce Type: cross Abstract: The recently envisioned goal-oriented communications paradigm requires machine learning inference to be performed directly on wirelessly transferred d
arXiv:2608.27206v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) demonstrate exceptional visual reasoning capabilities, yet their inference costs escalate rapidly with the proliferation
arXiv:2608.26180v1 Announce Type: cross Abstract: Shopping assistants are shifting from ranked product lists toward structured decision support, where systems must synthesize shopper context, product
arXiv:2608.26962v1 Announce Type: new Abstract: Molecular crystal structure prediction (CSP) is important in pharmaceuticals, agrochemicals, and organic electronics, where subtle differences in molecu
arXiv:2608.26658v1 Announce Type: cross Abstract: Generative retrieval has demonstrated strong performance by directly generating product semantic identifiers (SIDs). Extending this paradigm to image
arXiv:2608.27343v1 Announce Type: new Abstract: This paper addresses the recovery of essay-scale republication and reuse from fragmented text-reuse evidence, a setting whose central challenge is pair-
arXiv:2608.26720v1 Announce Type: new Abstract: Robotic and edge intelligence systems operate in dynamic environments where data arrives continuously, requiring models to adapt while preserving previo
arXiv:2608.27178v1 Announce Type: new Abstract: Accurate rectal cancer segmentation from magnetic resonance imaging (MRI) is essential for adaptive radiotherapy and tumor response assessment, but depl
arXiv:2608.27085v1 Announce Type: new Abstract: We study the problem of decentralized, self-organized task sharing for a swarm of heterogeneous robots that collaborate in transportation or other objec
arXiv:2608.27345v1 Announce Type: cross Abstract: Recent video generation models are increasingly framed as world models. Many physical processes can unfold in more than one valid way. Therefore, a wo
PDF parsing is fun because there's an infinite variety of enteprise documents 📑. For each document category, there's a long tail of work to build more precise bounding boxes, confidence scores, and do
arXiv:2608.26951v1 Announce Type: cross Abstract: Feed-forward 3D Gaussian Splatting reconstructs an explicit Gaussian representation from multiple input images in one network execution, making 3D rec
arXiv:2608.27046v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) and other RL-style post-training paradigms have been used for aligning large language models (LL
arXiv:2608.27427v1 Announce Type: cross Abstract: Large language model (LLM) agents in governed organizations must let the persona (instructions, tone, self-presentation) evolve freely, while keeping