Knowledge catalogue
arXiv:2609.37090v1 Announce Type: new Abstract: Large multimodal models (LMMs) support diverse visual understanding and reasoning tasks but are often impractical to run entirely on resource-constraine
arXiv:2609.37272v1 Announce Type: new Abstract: Non-injective mappings in neural networks map distinct inputs to the same representation, thereby implicitly inducing equivalence relations in the input
arXiv:2609.36968v1 Announce Type: new Abstract: Unsupervised tabular anomaly detection (TAD) aims to identify anomalous rows in tabular data using normal training samples. While conventional methods r
arXiv:2609.37356v1 Announce Type: new Abstract: Generating optimization instances that are both feasible and computationally challenging is crucial for benchmarking solvers and training learning-based
arXiv:2609.37302v1 Announce Type: new Abstract: Deep vision models often degrade under distribution shift. Test-time adaptation can improve robustness but typically requires iterative optimization, hy
arXiv:2609.36432v1 Announce Type: new Abstract: LiDAR relocalization aims to estimate the global 6-DoF pose of a sensor in the environment. However, existing regression-based approaches often encounte
arXiv:2609.36165v1 Announce Type: cross Abstract: In this work, we develop a second-order optimization framework for physics-informed neural networks (PINNs) applied to high-dimensional parametric par
arXiv:2609.36182v1 Announce Type: new Abstract: Robot manipulation policies are usually trained under the assumption that a commanded action produces the same motion as it did during training even aft
arXiv:2609.36593v1 Announce Type: cross Abstract: Creating diverse physical simulations remains labor-intensive because assets, layout, physical parameters, motion, control, and rendering must be desi
arXiv:2609.37654v1 Announce Type: new Abstract: We present a method for generating high quality materials for 3D objects entirely in texture space. We finetune a video diffusion transformer for text-g
thank god for embed5. somehow Cohere is really good at not looking at your data while being the best at indexing it The Cohere Embeddings team has been cooking 🍳 Several key innovations in the model:
While AI has made plenty of inroads on people's phones and computers, it's largely failed in dedicated devices. But over the next year, two major AI companies, Meta and OpenAI, will attempt to change
arXiv:2609.37732v1 Announce Type: new Abstract: Instruction-based image editors insert objects, restyle scenes and render new viewpoints, but it is unknown which camera they assume when they paint int
arXiv:2609.36209v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as knowledge bases (KBs) due to the vast amount of knowledge they acquire during pre-training. While
arXiv:2609.32964v2 Announce Type: replace Abstract: Language models (LMs) often hallucinate by committing to confident answers rather than abstaining, even when they do not have enough information to
arXiv:2609.35910v1 Announce Type: cross Abstract: Adaptive perception spends extra computation on inputs where perception is expected to improve. When perception feeds a downstream decision system, a
arXiv:2609.36829v1 Announce Type: new Abstract: An executor can respond strongly to a change in a supplied plan's priority while showing a small change in the same information-selection probability wh
arXiv:2609.35860v1 Announce Type: cross Abstract: Sampling based consistency is widely used for hallucination detection, yet aggregate performance can conceal systematic differences in which errors ar
arXiv:2609.37330v1 Announce Type: new Abstract: Clearing fog, rain or snow from footage, or turning renders into photographs, must remove the source domain and keep the scene. Unpaired translators car
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. “We’re not going to shoot ourselves in the foot” over hack fal
arXiv:2609.38035v1 Announce Type: cross Abstract: We give an explicit solution to the five expert prediction with expert advice partial differential equation (PDE) in the finite-time horizon setting.
arXiv:2609.37824v1 Announce Type: new Abstract: Transformer language models build predictions through successive residual updates, but how their representations become specific to an eventual outcome
arXiv:2609.36118v1 Announce Type: new Abstract: Vision-language-action (VLA) policies connect a pretrained vision-language backbone to an action head through a latent interface, but which backbone lay
arXiv:2609.35869v1 Announce Type: new Abstract: Pre-tokenisation restricts which text fragments can become prediction units, but its compression cost is obscured when tokenisers are compared only unde
arXiv:2609.37498v1 Announce Type: new Abstract: Wikipedia aims to provide a unified, neutral record of history, yet its independent language editions often function as distinct epistemic communities,
arXiv:2609.36230v1 Announce Type: new Abstract: We study the dynamical behavior of tokens in transformers from a control-theoretic perspective. Our model includes the feed-forward layer present after
arXiv:2609.36434v1 Announce Type: new Abstract: Context tokens in a transformer-based language model can be absorbed into the model's weights as a multiplicative operator. We study this operator in th
arXiv:2609.36252v1 Announce Type: new Abstract: Closed-form recourse moves a rejected user along the unit gradient hat g of the classifier score f by the promised distance d_p=|f(x)|/|nabla f(x)|, at
arXiv:2609.36290v1 Announce Type: cross Abstract: We investigate the extent to which the Hamas attacks on Israel of October 7, 2023, have affected German social media debates about Judaism and Israel.
arXiv:2609.36484v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student to match the teacher's next-token distributions on the student's own trajectories and has yielded substant
arXiv:2609.37914v1 Announce Type: cross Abstract: Fine-tuning large language models on narrow, misaligned tasks can undo their post-training alignment and induce novel misaligned behaviors -- a phenom
arXiv:2609.36069v1 Announce Type: cross Abstract: Generative AI (Gen AI) is reshaping how individuals learn and work, but its consequences for collective knowledge, the shared body of knowledge that o
arXiv:2609.36302v1 Announce Type: new Abstract: While foundation models have revolutionized natural language processing and computer vision by leveraging universal vocabularies, Graph Machine Learning
arXiv:2609.37161v1 Announce Type: new Abstract: Noise robustness in automated phonocardiogram (PCG) murmur detection, and how it is measured, remains underexamined despite growing interest in low-reso
arXiv:2609.36448v1 Announce Type: new Abstract: Transformers have demonstrated remarkable in-context learning (ICL) capabilities, enabling them to perform new tasks without additional fine-tuning. How
arXiv:2609.36243v1 Announce Type: cross Abstract: Full-page blind restoration of historical Manchu manuscripts is challenging due to scarce annotations, unknown degradation regions, and fragile connec
arXiv:2609.37372v1 Announce Type: new Abstract: Visual reward models are essential for evaluating and improving visual generation models, yet existing approaches typically map task conditions and cand
arXiv:2512.03284v2 Announce Type: replace Abstract: Spatial reasoning in large-scale 3D environments remains challenging for current vision--language models, which are typically constrained to room-sc
arXiv:2609.38147v1 Announce Type: new Abstract: As agents take on longer and more complex problems, controlling the execution becomes a task in its own right. Each step in the run brings new control c
arXiv:2609.37818v1 Announce Type: cross Abstract: Empathetic spoken dialogue requires models to use both what is said and how it is said to decide how to respond. Explicit CoT can improve paralinguist
arXiv:2609.36562v1 Announce Type: cross Abstract: While Multimodal Large Language Models (MLLMs) are increasingly deployed in safety-critical domains, their reliability is threatened by multimodal imp
arXiv:2609.36120v1 Announce Type: cross Abstract: Learned rotations play an important role in enabling low-bit weight and activation quantization of large language models by smoothing outliers in the
this should be fraud. certainly taxpayers shouldn’t be subsidizing Meta’s data centers. 🦔Meta classified its AI data centers as 'experimental pilot facilities' on its tax return. That let the Nvidia c
This story is so enraging. When you see mark zuckerberg bootlicking and bribing Trump, it’s for protection from the consequences of corrupt shit like this. how the American taxpayer helps back Meta's
arXiv:2609.36340v1 Announce Type: new Abstract: High-stakes advisory domains such as medical aesthetics, legal consultation, and educational planning exhibit a two-phase structure. The early phase req
arXiv:2609.37924v1 Announce Type: cross Abstract: Recent work on anchored diffusion language models improves denoising by shaping an intermediate latent space with supervised important-token targets.
Timelines just got shorter... AI will understand the physical 3D space better than humans by November* Is Google so back? Their new Gemini 4 Argon understands the physical 3D world better than any oth
To make it clear, Getty Images revenue went up the last three years not down from 917m in 2023 to 981m last year with 30% EBITDA margin. Their stock photo business dropped a bit, offset by editorial a
Today we're announcing Praxis-1, an open-weight world action model that adapts to new robot embodiments with light finetuning. Video is eating the world Introducing Praxis-1, an open-weight World Acti
arXiv:2609.37605v1 Announce Type: new Abstract: Supervised deep learning has advanced sparse-view tomographic reconstruction. However, conventional models, which typically map filtered back-projection
arXiv:2609.37196v1 Announce Type: cross Abstract: Tool-using LLM agents remain vulnerable to indirect prompt injection because trusted instructions and untrusted observations share one context, allowi
Top tech executives met with President Donald Trump on Tuesday to discuss the future of artificial intelligence amid growing concerns over AI models losing control. Researchers and lawmakers are calli
arXiv:2609.37884v1 Announce Type: new Abstract: Topological structures such as simplicial complexes, hypergraphs, and cell complexes extend standard graph models by modeling higher-order relationships
arXiv:2609.37953v1 Announce Type: new Abstract: Complex tasks inherently couple workflow structure, agent responsibility, collaboration, and memory access: task regions delimit responsibility and tool
arXiv:2609.36032v1 Announce Type: cross Abstract: Uniform random rotations are an effective preprocessing step for quantization: they make normalized coordinate distributions approximately Gaussian, e
arXiv:2609.35150v1 Announce Type: cross Abstract: Successful intercultural communication requires more than grammatical competence. It demands sensitivity to culturally embedded social norms whose vio
arXiv:2609.36323v1 Announce Type: new Abstract: AI-assisted coding tools deliver significant acceleration of coding, but only limited impact across the end-to-end software development lifecycle (SDLC)
arXiv:2609.36816v1 Announce Type: new Abstract: Reinforcement learning (RL) has become a cornerstone for improving the reasoning capabilities of large language models (LLMs), but the need for on-polic
arXiv:2609.36502v1 Announce Type: cross Abstract: Past research using log data has faced the 'learning system wall,' whereby few methods exist for generalizing models of student learning across platfo
arXiv:2609.36254v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) are commonly trained with reinforcement learning (RL) to improve their generation of chain-of-thought (CoT) reasoning befo