Knowledge catalogue
arXiv:2608.03591v1 Announce Type: cross Abstract: Large Language Model (LLM) agents offer a promising approach to attack chain reconstruction by retrieving and interpreting heterogeneous telemetry to
arXiv:2604.06005v2 Announce Type: replace Abstract: Interpreting the information encoded in language model weights remains a fundamental challenge in mechanistic interpretability. In this work, we int
arXiv:2608.03297v1 Announce Type: new Abstract: A standard claim in the literature on retrieval-augmented and memory-augmented language models is that shorter context is better when the relevant infor
arXiv:2608.03177v1 Announce Type: new Abstract: How can question answering (QA) systems determine whether a query is ambiguous? Ambiguity detection is essential in open-domain QA, as misclassification
Document OCR is not Getting Commoditized (by Frontier Models) The most common question I get is whether frontier models are going to eat all document processing solutions - just screenshot the page an
arXiv:2608.03791v1 Announce Type: new Abstract: Vision-Language Models (VLMs), like Large Language Models (LLMs), may memorize sensitive, copyrighted, or harmful knowledge from their pretraining corpo
arXiv:2510.11834v3 Announce Type: replace-cross Abstract: Generative models are increasingly paired with safety classifiers that filter harmful or undesirable outputs. A common strategy is to fine-tun
arXiv:2608.02673v1 Announce Type: cross Abstract: Speech editing for content creation requires precise control over both what an edit should do and where it should apply. Free-form natural language pr
arXiv:2608.03111v1 Announce Type: new Abstract: Double descent is commonly studied by scaling an explicit capacity parameter, such as neural-network width. For gradient boosting decision trees (GBDTs)
arXiv:2608.03130v1 Announce Type: cross Abstract: Long-term memory enables persistent personalization in LLM agents, but repeated memory-conditioned responses can cumulatively reveal protected attribu
arXiv:2608.03883v1 Announce Type: new Abstract: This paper describes our submissions to eRisk 2026 Task 3, ADHD Symptom Sentence Ranking. The task requires systems to rank candidate Reddit sentences a
arXiv:2608.03437v1 Announce Type: new Abstract: While human evaluation is the gold standard in many NLP tasks, it suffers from prohibitive costs and poor scalability. When identifying top-performing m
arXiv:2608.03179v1 Announce Type: new Abstract: Controllable local editing of 3D assets requires precise target localization and appropriate visual guidance. However, existing methods lack a simple ye
arXiv:2608.03206v1 Announce Type: cross Abstract: Large language models (LLMs) power educational applications from tutoring to essay scoring, but each is a point solution to a single task, and only re
arXiv:2608.03796v1 Announce Type: cross Abstract: Small language models are often the only option for deployment under tight latency, cost, and on-premises constraints, but they are rarely trained fro
arXiv:2608.03480v1 Announce Type: new Abstract: The adoption of large pre-trained multilingual models for neural machine translation (MNMT) faces a major challenge: excessive memory and computational
arXiv:2407.21311v2 Announce Type: replace-cross Abstract: Unsupervised domain adaptation (UDA) aims to mitigate domain shift, where the distribution of labeled source data differs from that of unlabel
arXiv:2608.03565v1 Announce Type: new Abstract: While modern tabular learners excel at capturing statistical patterns, they frequently operate in a semantic vacuum, treating textual features as discre
arXiv:2608.03028v1 Announce Type: new Abstract: Applying a valid medication-safety rule when its patient-specific conditions are not met can produce an incorrect decision. Existing medical evaluations
arXiv:2608.03311v1 Announce Type: cross Abstract: Enterprise compliance management requires rapid adaptation to evolving regulatory frameworks (e.g., DORA, AI RMF, FedRAMP) and tight remediation SLAs.
arXiv:2608.03794v1 Announce Type: cross Abstract: Large Language Models (LLMs) are transforming database interaction paradigms, evolving from simple query translators to autonomous database administra
arXiv:2608.02616v1 Announce Type: cross Abstract: We present the first independent, systematic evaluation of OpenAI's Privacy Filter (OPF), a 1.5B-parameter bidirectional PII detector, across 42 synth
arXiv:2608.02786v1 Announce Type: new Abstract: AI systems can fail silently. The failure propagates through training loops, evaluation pipelines, and production monitoring stacks until downstream har
arXiv:2608.03045v1 Announce Type: new Abstract: We consider grey-box optimization problems where the decision variables naturally partition into black-box variables (as arguments to an expensive black
arXiv:2511.15968v2 Announce Type: replace-cross Abstract: External validation of breast ultrasound segmentation models remains limited because internal train--test splits do not capture domain shifts
arXiv:2608.03222v1 Announce Type: cross Abstract: Software engineering (SWE) agents resolve repository-level issues through long trajectories that grow increasingly expensive as context accumulates. F
arXiv:2608.03096v1 Announce Type: cross Abstract: Recent advances in video generation models have significantly intensified the deepfake threat, yet the current deepfake video detection benchmarks rem
arXiv:2608.03852v1 Announce Type: new Abstract: This paper proposes FedCritic-MIMO, a communication-efficient serverless federated multi-agent reinforcement learning framework for AI-native resource c
Feels like Google could have been the dominating force in AI by open-sourcing the frontier with Gemini, Veo, and Nano Banana. Instead, they kept them behind APIs for a few billion dollars in revenue.
arXiv:2608.03259v1 Announce Type: cross Abstract: As time-series foundation models have emerged, the need for benchmarks that can evaluate their forecasting ability in meaningful ways has become incre
arXiv:2608.02919v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in complex, compound AI systems where performance hinges on the quality of prompts. Recent state-
arXiv:2608.02911v1 Announce Type: new Abstract: Revenue forecasts guide acquisition budgets, demand planning, and customer-based valuations, yet an aggregate forecast does not show whether change refl
... four years later, I got the new Claude Fable 5 to actually build the game https://x.com/simonw/status/2085089518223602058 Four years ago today I tweeted about having GPT-3 and DALL-E come up with
arXiv:2608.03385v1 Announce Type: new Abstract: Existing object detection methods predominantly utilize sRGB inputs, which are compressed from RAW sensor data using Image Signal Processors (ISP) origi
arXiv:2508.00955v3 Announce Type: replace-cross Abstract: Adapting generative Multimodal Large Language Models (MLLMs) into universal embedding models typically demands resource-intensive contrastive
arXiv:2608.03585v1 Announce Type: new Abstract: Open-source software communities are a form of digital public infrastructure that not only produces code, but also generates public knowledge and interp
arXiv:2608.03136v1 Announce Type: new Abstract: Cross-city object detection requires a detector trained in one city to generalize to an unlabeled target city. In AI City Challenge 2026 Track 6, we ana
arXiv:2603.08199v2 Announce Type: replace Abstract: LiDAR-camera 3D multi-object tracking (MOT) combines rich visual semantics with accurate depth cues to improve trajectory consistency and tracking r
arXiv:2608.03764v1 Announce Type: new Abstract: Agent self-evolution updates an agent's persistent state from prior experience and reuses it to solve related tasks more effectively. Evaluating self-ev
arXiv:2608.03868v1 Announce Type: cross Abstract: Causal Discovery (CD) from observational data faces two fundamental challenges. First, purely statistical methods often lack the power to resolve stru
arXiv:2608.03826v1 Announce Type: new Abstract: Geospatial and urban applications increasingly require models to compare heterogeneous evidence across street-view imagery, remote-sensing observations,
arXiv:2608.03071v1 Announce Type: new Abstract: Large language model agents derive much of their capability from tool use. Existing research on tool use has largely focused on selecting the right tool
arXiv:2608.02877v1 Announce Type: new Abstract: Causal discovery recovers directed structure from observational data and is increasingly used in clinical settings to support mechanism reasoning and fa
arXiv:2608.03270v1 Announce Type: cross Abstract: GUI grounding maps natural-language instructions to click locations and is essential for reliable GUI agents. The task remains difficult on high-resol
Ivan Mehta / TechCrunch: Hark, founded by Figure AI CEO Brett Adcock, previews Handoff, a computer use agent it says outperforms GPT-5.4 and Opus 4.8, and plans for a summer release — Hark, a startup
Harness choice is a big deal. So much room to advance and improve results across the board with agent harnesses. Great paper highlighting this. New research releases DataSpace, a benchmark where data
Hey everyone! I just released a sub-6B sparse activation AI model which was built with a brand new architecture : fusion. I fused weights from @liquidai's LFM2.5-2.6B & @Alibaba_Qwen's Qwen3.6-35B-A3B
arXiv:2509.23690v2 Announce Type: replace-cross Abstract: Safety hazards in the home are a leading cause of preventable domestic injuries, motivating an automated inspector that actively explores a ho
arXiv:2608.03659v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to generate scientific reviews, yet existing evaluations rarely examine whether different providers
arXiv:2604.04790v2 Announce Type: replace Abstract: Natural language processing (NLP) advances have powered a generation of LegalTech systems, but Turkish law remains under-served by domain-specific d
arXiv:2608.02967v1 Announce Type: cross Abstract: Software fault localization identifies the code locations responsible for reported issues and is a fundamental step toward automated debugging and pro
arXiv:2603.26468v2 Announce Type: replace Abstract: The rapid growth of hyperspectral data archives in remote sensing (RS) necessitates effective compression methods for storage and transmission. Rece
I mean, Deepseek V4 Flash is an absolutely fantastic model, even though I can't run it on my machine it's so fascinating to see how it performs. Knowing that potentially it could be run at home is rea
It's the purple cluster on the top left (the good corner...) I'm running the MXFP4 version from Bartoswski with Dspark at 1K t/s prefill and 90 t/s gen (average). I tried different sampling params, yo
arXiv:2608.02830v1 Announce Type: cross Abstract: Many-shot in-context learning (ICL) lets vision-language models (VLMs) adapt from image--label demonstrations without weight updates, and is widely as
arXiv:2602.17976v2 Announce Type: replace-cross Abstract: In active sequential testing, also termed pure exploration, a learner is tasked with the goal to adaptively acquire information so as to ident
Incident Report: unsanctioned agent behaviour during cyber testing It happened again. This time it was the UK government's AI Security Institute who accidentally attacked other companies while running
A follow up to the launch of Mference, it now supports and runs Inkling-Small 276B-A12B. Inkling-Small (Thinking Machines, Apache 2.0), from the pipenetwork/Inkling-Small-MLX-4bit conversion: 276B tot
arXiv:2608.02639v1 Announce Type: cross Abstract: Production prompts rarely carry a single instruction. One system message may require valid JSON, a word limit, three citations, and a fixed tone at th
arXiv:2608.03138v1 Announce Type: cross Abstract: Generating a rigorous paper introduction with large language models (LLMs) remains challenging, since it requires coordinating background, gap identif