Knowledge catalogue
arXiv:2603.15106v2 Announce Type: cross Abstract: Enabling efficient deep neural network (DNN) inference on edge devices with different hardware constraints is a challenging task that typically requir
arXiv:2609.36376v1 Announce Type: cross Abstract: Dense retrieval, the key component of Retrieval Augmented Generation (RAG), retrieves the most relevant documents by comparing dense vector representa
arXiv:2609.37688v1 Announce Type: new Abstract: Reading behaviour varies not only with linguistic input, but also with reader proficiency. In this study, we investigate whether the layer-wise relation
arXiv:2609.36984v1 Announce Type: new Abstract: Complex questions often require multi-hop reasoning that connects facts distributed across sources or distant regions of a long context through intermed
arXiv:2609.36822v1 Announce Type: new Abstract: The rapid evolution of image generators calls for forensic cues that generalize beyond known generation mechanisms. Existing detectors often rely on sta
arXiv:2609.36348v1 Announce Type: cross Abstract: Generative and representation learning remain asymmetrically connected: semantic representations are used to improve diffusion generation, whereas the
arXiv:2511.11164v3 Announce Type: replace Abstract: Bridging the past to the future, connecting agents both spatially and temporally, lies at the core of the trajectory prediction task. Despite great
arXiv:2609.36393v1 Announce Type: cross Abstract: Traditional reinforcement learning (RL) techniques focus on maximizing expected cumulative reward, where each action assumes to take a constant unit o
arXiv:2609.36875v1 Announce Type: new Abstract: Accurate instance segmentation in dynamic scenes is important for downstream applications such as robotics and autonomous driving. Existing Segment Anyt
arXiv:2609.37298v1 Announce Type: cross Abstract: Conformal prediction provides set-valued predictions with distribution-free coverage guarantees, making it attractive for high-stakes image classifica
arXiv:2609.36614v1 Announce Type: new Abstract: A commercial incentive need not enter the final ranking algorithm to affect a shopping assistant's recommendation: it may instead influence which prefer
arXiv:2609.37539v1 Announce Type: new Abstract: Skills equip LLM agents with professional knowledge and guidance to complete long-horizon and complex tasks. Although skills have been widely adopted in
So I would like to share my analysis of PD disagg that I've run by Horace and many folks at Thinky You may have heard that PD disagg helps with per-token 'tail latencies' in ITL/TPOT, as prefill inter
arXiv:2609.37730v1 Announce Type: new Abstract: Seizure detection and prediction from EEG are clinically important but challenging because seizures are rare, temporally localized, and propagate as coo
arXiv:2609.36271v1 Announce Type: new Abstract: Recent work has established that power-law spectral conditions on data enable tight convergence bounds for deterministic gradient descent, resolving the
arXiv:2609.38096v1 Announce Type: new Abstract: Policies with similar mean returns can differ sharply in rare failures, yet estimating lower-tail conditional value-at-risk (CVaR) accurately can requir
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:2609.36432v1 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:2609.36182v1 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:2609.37654v1 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
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:2609.36448v1 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:2609.36323v1 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:2609.36530v1 Announce Type: new Abstract: Motion planning often admits multiple feasible solutions, making multimodal generation valuable, particularly for flexible multi-robot coordination. Dif
arXiv:2609.37082v1 Announce Type: new Abstract: Long-horizon information-seeking agents often accumulate noisy or misleading context, causing early mistakes to persist and making recovery increasingly
arXiv:2609.36678v1 Announce Type: new Abstract: Private Evolution (PE) is a differentially private algorithm for synthetic data generation. While it can be viewed as a Wasserstein learning algorithm,
arXiv:2609.37950v1 Announce Type: new Abstract: Video understanding agents acquire evidence through an executable harness that controls what they observe and how they use those observations. However,
arXiv:2609.37648v1 Announce Type: new Abstract: Preoperative liver-tumor assessment requires segmentation, physical-space measurement, visual evidence, and resection planning from the same three-dimen
arXiv:2609.36887v1 Announce Type: new Abstract: Recent efforts to scale tool-use post-training have largely centered on the synthesis of executable environments, which constitute only one component of
arXiv:2609.38121v1 Announce Type: new Abstract: KV cache memory and bandwidth costs grow with context length and batch size, which limits efficient long-context inference. To address this bottleneck,
🚨 Yesterday, the 'White House Accord on Super Intelligence' was signed. What was supposed to be about AI safety and accountability was instead a PROBLEMATIC endorsement of self-regulation. My comments
arXiv:2609.31686v1 Announce Type: new Abstract: Existing aviation emissions inventories lack accurate trajectory data for high-resolution social cost and health impact assessment. This paper develops
arXiv:2609.35121v1 Announce Type: new Abstract: Patient responses to dental pulp testing, ranging from no sensation to intense pain, provide important information for assessing pulp status in endodont
arXiv:2609.35703v1 Announce Type: new Abstract: Reliable deployment of graph neural networks requires calibration, out-of-distribution (OOD) detection, and robustness to distribution shift, yet existi
arXiv:2510.26672v2 Announce Type: replace-cross Abstract: At the heart of reinforcement learning are actions -- decisions made in response to observations of the environment. Actions are equally funda
arXiv:2609.32252v1 Announce Type: cross Abstract: Acquiring data is costly: higher measurement fidelity costs power and storage and risks collecting irrelevant content, while aggressive cost reduction
arXiv:2609.34281v1 Announce Type: new Abstract: High-dimensional Bayesian optimization (HDBO) seeks sample-efficient optimization when the number of variables is large relative to the evaluation budge
arXiv:2609.34823v1 Announce Type: new Abstract: Augmented dexterity has the potential to reduce the fatigue experienced by surgeons during repetitive surgical tasks. In this paper, we propose the firs
'The chance of human extinction is about a coin flip, in my view,' Geoffrey Irving, a former OpenAI and Google DeepMind employee, said in a new interview. It's one of a dozen interviews with AI resear
arXiv:2609.32740v1 Announce Type: new Abstract: Intraoperative anesthesia requires systems to interpret evolving multimodal evidence, recommend timely management, and revise decisions as patient state
arXiv:2607.09948v2 Announce Type: replace-cross Abstract: Cardiac amyloidosis (CA) is increasingly recognized but remains substantially underdiagnosed because its clinical and imaging phenotype overla
arXiv:2506.08140v2 Announce Type: replace Abstract: Despite long-standing efforts in accelerating scientific discovery with AI, building AI co-scientists remains challenging due to limited high-qualit
arXiv:2601.10214v3 Announce Type: replace Abstract: Camera control has been extensively studied in conditioned video generation; however, performing precisely altering the camera trajectories while fa
arXiv:2609.35635v1 Announce Type: new Abstract: In materials machine learning, closely related retained structures can sustain accurate property predictions even after removing a specific record, rend
BREAKING: OpenAI postpones 6.1 for safety reasons. If we can take OpenAI at face value, this is quite a decision—and also a sign that no magical solution is in immediate view. Per @sheeraf at NYT “GPT
arXiv:2511.12257v2 Announce Type: replace-cross Abstract: This paper proposes a novel Bayesian framework for solving Poisson inverse problems by devising a Monte Carlo sampling algorithm which account
arXiv:2609.31978v1 Announce Type: cross Abstract: Generating independent, equilibrium samples of molecular systems at scale remains a central obstacle in computational statistical mechanics. Boltzmann
Manually extracting data from hundreds of vendor contracts doesn't scale, and RAG chat tools fall short on portfolio-wide questions. This post shares a contract intelligence platform on AWS that uses
arXiv:2609.32167v1 Announce Type: new Abstract: Counterfactual prediction estimates an individual's outcome under an alternative intervention given their factual observations. Such outcomes are genera
arXiv:2609.34246v1 Announce Type: new Abstract: Autoregressive neural emulators can drift or diverge over long rollouts despite accurate short-term predictions. We introduce Cascaded Emulation (CasEm)
arXiv:2609.33003v1 Announce Type: new Abstract: Vision-language verifiers and routers must distinguish errors repairable by more reasoning from those caused by visual evidence never reaching the langu
arXiv:2609.34439v1 Announce Type: new Abstract: Medical vision-language pre-training largely follows a visit-level image-report matching paradigm, aligning paired images and reports at individual visi
arXiv:2609.35619v1 Announce Type: new Abstract: Incorporating dense visual information into motion planning remains challenging, as geometric planners rely on abstracted scene representations that dis
arXiv:2604.01601v2 Announce Type: replace Abstract: In-context fine-tuning (IC-Train), training an LLM with labeled examples in-context, is increasingly used in place of standard fine-tuning for domai
arXiv:2609.34183v1 Announce Type: new Abstract: Weakly Supervised Semantic Segmentation (WSSS) learns pixel-level predictions from image-level tags. Recent work focuses on improving coarse CAMs extrac
arXiv:2609.31696v1 Announce Type: cross Abstract: Offline evaluation is the dominant experimental paradigm in recommender systems research, enabling reproducible and cost-effective comparisons on hist
arXiv:2609.33653v1 Announce Type: cross Abstract: Reinforcement learning (RL) enables generalist robot policies to improve through trial-and-error interaction, yet its effectiveness is fundamentally c
arXiv:2508.15641v2 Announce Type: replace Abstract: Precise temporal grounding requires distinguishing when a queried event occurs from when its participating entities are merely visible. We propose D
OpenAI introduced “Dots,” an AI system built to run continuously and free users’ time so they can focus on higher‑level tasks. The announcement was posted on September 29 2026 by CEO Sam Altman via Tw