Knowledge catalogue
arXiv:2606.28328v1 Announce Type: cross Abstract: In recent years, text clustering has become a critical technique for applications including intent discovery, topic mining, and recommendation systems
arXiv:2606.30442v1 Announce Type: new Abstract: The Bitter Lesson, which posits that general-purpose methods that scale with computation and data ultimately outperform those with built-in human knowle
arXiv:2606.28327v1 Announce Type: cross Abstract: How do retrieval bounds compare between human episodic memory and Retrieval-Augmented Generation (RAG) systems under semantic interference? We present
arXiv:2606.29526v1 Announce Type: new Abstract: Reinforcement learning (RL) has gained growing attention in large language model (LLM) post-training, yet RL training remains fragile and can suffer fro
arXiv:2606.29503v1 Announce Type: cross Abstract: The verbose context problem occurs when structured concepts have token-inefficient textual representations. This bottleneck is acute in population hea
arXiv:2606.29841v1 Announce Type: new Abstract: Continual learning (CL), where a model is trained on a sequence of data tasks, is increasingly being adopted across key fields such as large language mo
arXiv:2512.10359v1 Announce Type: cross Abstract: Video Question Answering (VideoQA) task serves as a critical playground for evaluating whether foundation models can effectively perceive, understand,
arXiv:2606.30560v1 Announce Type: cross Abstract: Coding agents are rapidly becoming a major application of agentic LLMs, but serving them efficiently remains challenging. Progress on this challenge r
arXiv:2606.28716v1 Announce Type: new Abstract: The robustness of trajectory prediction models is crucial for developing safe autonomous driving systems. Adversarial attacks on trajectory prediction c
arXiv:2606.28659v1 Announce Type: cross Abstract: High-fidelity molecular docking simulations can produce biologically relevant estimates of epitope-receptor binding affinity but are computationally e
arXiv:2605.05522v2 Announce Type: replace-cross Abstract: Although self-supervised pretraining is expected to learn broadly transferable representations, its effectiveness across imaging modalities su
arXiv:2606.28548v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) have become a useful tool for extracting interpretable features in language models. However, standard SAE architectures opera
Tutorial on using Gemini live to build a voice agent Uses deepagents as a tool: offload complex work to this subagent, use Gemini live for the naturalness/latency Building voice agents can come with t
arXiv:2606.30578v1 Announce Type: new Abstract: With rapidly improving capabilities, Large Language Models (LLMs) are increasingly used in many complex real-world tasks. Beyond requiring in-depth know
arXiv:2606.29781v1 Announce Type: new Abstract: Urban building change detection from bi-temporal aerial imagery is important for redevelopment monitoring, infrastructure management, and unauthorized-c
arXiv:2606.28401v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have shown strong performance in visual understanding, yet they still suffer from hallucinations, generating content that
arXiv:2606.30288v1 Announce Type: new Abstract: Large Vision Language Models (LVLMs) have achieved remarkable success on vision-language tasks, yet fine-grained perception over high-resolution images
We’ve received notice that the Department of Commerce has lifted export controls on Claude Fable 5 and Mythos 5. We'll begin restoring access tomorrow, and will share an update soon. We’re grateful to
arXiv:2603.02491v3 Announce Type: replace-cross Abstract: As artificial agents become increasingly capable, what internal structure is necessary for an agent to act competently under uncertainty? Clas
arXiv:2606.28469v1 Announce Type: new Abstract: Robot initiative is a central challenge in multi-party human-robot collaboration. A robot that contributes without being addressed may provide timely su
arXiv:2510.03164v2 Announce Type: replace Abstract: Learning rate warm-up -- increasing the learning rate at the beginning of training -- has become a ubiquitous heuristic in modern deep learning, yet
arXiv:2606.14752v2 Announce Type: replace-cross Abstract: Modern Vision-Language-Action (VLA) models must bridge pretrained vision-language reasoning and precise continuous robot control. Existing act
You cannot ban Chinese open source to make US win. The whole point of open source is it's OPEN. You might ban in the US, sure, but how are you going to ban it outside US? Instead the real question is,
arXiv:2606.29208v1 Announce Type: new Abstract: Pose histories provide the core kinematic evidence for 3D human motion prediction, but they lack explicit high-level semantic guidance. This paper intro
arXiv:2602.00334v2 Announce Type: replace Abstract: Momentum Stochastic Gradient Descent (mSGD) relies on a fixed momentum coefficient shared across all parameters, failing to account for the heteroge
arXiv:2606.27543v1 Announce Type: cross Abstract: The variations in vocal effort range (e.g. whisper, soft, neutral, loud, shout) alter production and speech acoustics, reducing intelligibility and li
arXiv:2606.27959v1 Announce Type: new Abstract: Factual Error Detection (FED), which is the task of identifying factually incorrect spans in a given text, has long been recognized as an important rese
arXiv:2606.27446v1 Announce Type: new Abstract: This paper describes team HSA_CORAL's submission to the FinCausal 2026 shared task on extracting cause-effect relations from financial narratives via ex
arXiv:2510.16492v4 Announce Type: replace Abstract: As Large Language Model (LLM) agents increasingly operate in complex environments with real-world consequences, their safety becomes critical. While
arXiv:2511.02340v3 Announce Type: replace Abstract: Chronic Kidney Disease (CKD) affects nearly 10% of the global population and often progresses to end-stage renal failure. Accurate prognosis predict
arXiv:2606.28186v1 Announce Type: cross Abstract: Predicting human item difficulty is central to educational assessment, where reliable estimates support fairness and effective test construction. Exis
arXiv:2603.26629v2 Announce Type: replace Abstract: Multimodal fusion requires integrating information from multiple sources that may conflict depending on context. Existing fusion approaches typicall
arXiv:2606.27935v1 Announce Type: new Abstract: Deep learning has demonstrated remarkable success in high-throughput histopathology image analysis. However, the performance of learning-based models cr
arXiv:2606.28012v1 Announce Type: new Abstract: Change Detection (CD) aims to identify semantic or structural changes from nearly registered multi-temporal images. While recent advances in training me
arXiv:2606.27409v1 Announce Type: cross Abstract: Multi-agent large language model (LLM) systems often rely on verifier and critic agents to suppress hallucinations, but verification is delayed. Durin
arXiv:2606.27748v1 Announce Type: cross Abstract: Transformer models rely on attention mechanism to capture long-range dependencies but suffer from quadratic complexity, limiting their scalability to
arXiv:2606.27413v1 Announce Type: cross Abstract: Understanding which genes control which traits in an organism remains one of the central challenges in biology. Despite significant advances in data c
arXiv:2606.28242v1 Announce Type: cross Abstract: Understanding how performance scales jointly with model size and data is a central problem in modern machine learning. Existing theoretical works on s
arXiv:2511.07836v4 Announce Type: replace-cross Abstract: The curse of dimensionality remains a persistent challenge in modern optimization problems. Expanding the search space into higher dimensions
arXiv:2601.21233v2 Announce Type: replace Abstract: Autonomous code agents built on large language models are reshaping software and AI development through tool use, long-horizon reasoning, and self-d
arXiv:2601.12066v4 Announce Type: replace Abstract: Existing video object removal methods predominantly rely on diffusion models following a noise-to-data paradigm, where generation starts from uninfo
arXiv:2510.25731v2 Announce Type: replace-cross Abstract: Initial-boundary value problems (IBVPs) provide the essential framework for modelling a wide range of phenomena in physics and engineering. We
arXiv:2606.28024v1 Announce Type: new Abstract: Lifted inference exploits indistinguishabilities in probabilistic graphical models by using a representative for indistinguishable objects, thereby spee
arXiv:2606.27709v1 Announce Type: cross Abstract: Recent work has shown that fine-tuning large language models (LLMs) for social warmth degrades factual reliability and increases sycophancy. We invest
arXiv:2606.27412v1 Announce Type: cross Abstract: 3D Scene Graph Generation (3DSGG) represents 3D scenes as structured object-relation-object graphs, providing a compact relational abstraction for spa
arXiv:2606.27459v1 Announce Type: new Abstract: We consider the cubic nonlinear Schrodinger (NLS) equation on two-dimensional flat tori with varying aspect ratios. In this formulation, the choice of a
arXiv:2606.27440v1 Announce Type: new Abstract: Foundation models for structural biology have achieved remarkable performance in predicting biomolecular structure and show promise for the design of pr
arXiv:2606.28322v1 Announce Type: new Abstract: We introduce PerceptionRubrics, a rubric-based evaluation framework that addresses the gap between saturated benchmark scores and real-world brittleness
arXiv:2606.27379v1 Announce Type: cross Abstract: Large language models increasingly face demands to 'forget' training data, knowledge, or behaviors due to regulatory deletion obligations, copyright/l
arXiv:2502.16886v4 Announce Type: replace-cross Abstract: To reduce memory consumption during LLM inference, a handful of methods have been proposed for KV cache pruning. While these techniques can ac
arXiv:2606.27397v1 Announce Type: cross Abstract: Evaluating LLM agents requires dynamic environments that go beyond static reasoning and zero-sum games. Real-world economic interaction is often open-
arXiv:2606.27509v1 Announce Type: new Abstract: In this study, we develop a Structured framework for Gaussian Splatting (3DGS) with LiDAR integration (Structured-Li-GS). It is a lightweight Gaussian S
arXiv:2606.28077v1 Announce Type: new Abstract: In real-world deployments, scene text detectors inevitably face distribution shifts beyond the training distribution. Prior work often depends on large-
arXiv:2606.27510v1 Announce Type: cross Abstract: Activation patching is the primary tool in mechanistic interpretability. It attributes causal responsibility for a model behavior to each of its indiv
arXiv:2606.28013v1 Announce Type: new Abstract: Headline type-correctness (TC%) of LLM autoformalization has climbed from sim53% to sim76% in two years, yet this scalar conceals which errors each meth
arXiv:2606.28277v1 Announce Type: cross Abstract: Artificial intelligence is driving a revolution in scientific discovery, accelerating everything from hypothesis generation to mathematical theorem pr
arXiv:2510.00705v3 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) often struggle with fine-grained perception, such as identifying small objects in high-resolution images or
We just launched Comfy MCP in public beta, the first MCP built for production pipelines. Connect Claude, Codex, Cursor, or Hermes to the entire ComfyUI ecosystem. → Run any workflow in natural languag
Dcode does a bunch of work to standardize message format, making it easy to switch providers mid thread Claude Opus -> GLM 5.2 in under 10 seconds dcode isn't just provider-agnostic. it makes the cros
Zvi Mowshowitz / Don't Worry About the Vase: GPT-5.6 system card indicates Sol is well below the level of most worrisome Mythos use cases, suggesting all GPT-5.6 versions could be released without del