research

arXiv:2609.12875v1 Announce Type: new Abstract: Machine olfaction trains on pooled public descriptor corpora, but whether a shared descriptor word measures the same thing across corpora has not been t

arXiv:2609.12356v1 Announce Type: new Abstract: SNAP-KG is a framework for assigning newly arriving entities to semantic communities in a growing knowledge graph (KG) using only their raw features, wi

arXiv:2606.21203v2 Announce Type: replace Abstract: Psycholinguistics studies show that human readers fall for coherence illusions: an incoherent discourse can seem coherent simply because a distracto

arXiv:2609.12702v1 Announce Type: new Abstract: Capturing the digital trace of handwriting usually requires a specific stylus and a compatible substrate, be it a capacitive touchscreen, an ElectroMagn

2019: “GPT2 is groundbreaking in two ways. One is its size, says Dario Amodei, OpenAI’s research director. The models “were 12 times bigger, and the dataset was 15 times bigger and much broader” than

【AIの難問は、生命の難問へ：英国王立協会が紐解く「世界モデル」と知能の未来】 近年のAIの急速な発展により、AGI、すなわち人間並みの知能はすでに実現したという意見も聞かれるようになりました。果たしてそうなのでしょうか。 鍵となるのが「世界モデル（World Model）」の概念です。 世界モデルとは、生き物やAIが外の世界を内部に写し取り、次に何が起きるかを予測して行動するための土台となるもの

I must be among an extremely small group of people (n=1?) that have both 1) trained a frontier LLM and 2) designed and synthesized custom viruses in a lab with my own two hands. And I think that the t

Investors in Anthropic founded Open Philanthropy, the leading org promoting AI Doom They have a stake in regulation on AI that excludes competitors OP is the major funder of Tarbell Tarbell Fellows pe

Looped transformers are a popular architecture topic right now. This new technical report extends the loop across tokens. Recurrent Looped Transformer (RLT) makes the decoder recurrent over every toke

Sept 9, 2026 hits an all time daily high of 447 new machine learning papers uploaded to cs.LG (https://arxiv.org/list/cs.LG/recent?skip=0&show=500). This is many times more papers than what a human be

arXiv:2609.10579v1 Announce Type: cross Abstract: We present a machine-checked Lean~4 formalization of Dong and Yang's classification of optimal finite-length (n,4) binary block codes for binary symme

arXiv:2609.11713v1 Announce Type: cross Abstract: Artificial neural networks rely on vector-matrix multiplications (VMMs), whose implementation in von Neumann architectures is dominated by costly data

arXiv:2609.11498v1 Announce Type: new Abstract: Practical uncertainty quantification (UQ) for large language models must decide, from a single generation, whether a specific answer should be trusted.

arXiv:2609.11224v1 Announce Type: cross Abstract: Sports data analysts translate domain questions into insights by combining computation with sport-specific domain expertise. Large language models eas

arXiv:2609.11199v1 Announce Type: new Abstract: With the existing digital mental health tools specifically developed for Western settings, Pakistani students are exposed to a uniquely compounded stres

arXiv:2609.10707v1 Announce Type: cross Abstract: The integration of Large Language Models (LLMs) into Security Operations Centers (SOCs) streamlines threat intelligence but introduces critical vulner

arXiv:2609.11170v1 Announce Type: new Abstract: Temporal graph counterfactual explanations typically change past events to change or invalidate an original prediction, while leaving its replacement un

arXiv:2609.11391v1 Announce Type: cross Abstract: Environmental controversies in global supply chains pose significant risks for global buyers. This study examines whether overseas suppliers' exposure

arXiv:2609.11446v1 Announce Type: new Abstract: Heterogeneous model collaboration seeks to exploit the complementary strengths of different models to balance predictive performance and inference cost.

arXiv:2607.09489v2 Announce Type: replace Abstract: An AI system's output is not the fact or world state it appears to describe, but rather an engineered representation. We propose a semantic framewor

arXiv:2609.11373v1 Announce Type: cross Abstract: Empirical research on content moderation is fundamentally constrained by the opaque deployment of moderation systems on major social media platforms.

arXiv:2609.11404v1 Announce Type: cross Abstract: This paper presents DF-CAPTCHA, an active defense against real-time deepfake impersonation in voice and video calls. Instead of passively searching fo

arXiv:2506.14045v2 Announce Type: replace Abstract: Developing agents capable of exploring, planning and learning in complex open-ended environments is a grand challenge in artificial intelligence (AI

arXiv:2609.11341v1 Announce Type: new Abstract: Multimodal brain state decoding has largely focused on fusing paired modalities for prediction, but has rarely explored how their correspondence can be

arXiv:2609.11182v1 Announce Type: cross Abstract: In classical pattern recognition tasks, neural networks are trained to recognise human-defined patterns for model inputs. Some Explainable AI (XAI) me

arXiv:2609.11509v1 Announce Type: new Abstract: Quantifier instantiation is currently the main approach to non-ground SMT solving: solvers generate ground instances and solve the resulting ground SMT

arXiv:2609.11458v1 Announce Type: new Abstract: Determining the differences between two speakers' accents is a fundamental task in linguistics and speech technology research. The methodology used to m

arXiv:2603.29944v3 Announce Type: replace-cross Abstract: Quantum sensing technologies offer transformative potential for ultra-sensitive biomedical sensing, yet their clinical translation remains con

arXiv:2604.06015v2 Announce Type: replace Abstract: Instruction tuning is commonly assumed to endow language models with a domain-general ability to follow instructions, yet the underlying mechanism r

I love this and really hope we can come together as an industry and make it happen. We Must Pace the Frontier: I’ve written a new essay on why the AI industry should slow down, with a three-part plan

arXiv:2609.11447v1 Announce Type: cross Abstract: This work investigates a number of approaches to prevent catastrophic forgetting in class incremental learning scenarios for sound event classificatio

arXiv:2609.11066v1 Announce Type: cross Abstract: In conversational AI, detecting when a speaker has finished talking is crucial for natural turn taking. While recent work incorporates semantics, the

arXiv:2609.11876v1 Announce Type: new Abstract: Recently, a wide range of recommendation algorithms inspired by deep learning techniques have emerged as the performance leaders on several standard rec

arXiv:2603.09309v3 Announce Type: replace Abstract: Verbalized confidence, in which LLMs report a numerical certainty score, is widely used to estimate uncertainty in black-box settings, yet the confi

arXiv:2609.11452v1 Announce Type: new Abstract: Efficient routing optimization is essential to freight transportation, urban logistics, and shared mobility, where high-quality heuristics are often req

arXiv:2609.11315v1 Announce Type: new Abstract: Diffusion vision-language models generate answers through iterative refinement, exposing intermediate answer trajectories that can be inspected and cont

arXiv:2609.11667v1 Announce Type: cross Abstract: In this paper, we develop warrant theory as a philosophical discipline concerned with the inferential legitimacy of propositions within logical analys

arXiv:2609.11211v1 Announce Type: cross Abstract: Deep learning models, notably Long Short-Term Memory (LSTM), have demonstrated promising performance in channel estimation for high-mobility vehicular

arXiv:2609.11894v1 Announce Type: new Abstract: Solving novel view synthesis (NVS) for millimeter-wave (mmWave) radar requires a renderer that is physically faithful, complex-valued, and multi-viewpoi

arXiv:2609.11550v1 Announce Type: new Abstract: Early diagnosis of melanoma is critical for improving patient survival rates. However, accurately distinguishing melanoma from other skin lesions remain

arXiv:2609.06470v2 Announce Type: replace-cross Abstract: To solve the fractional knapsack problem, Dantzig's greedy rule orders items according to their value-to-cost ratio. This ordering introduces

arXiv:2609.10654v1 Announce Type: cross Abstract: The Abstraction and Reasoning Corpus (ARC) benchmarks cognitive generalization, the ability to infer and apply abstract rules from limited examples. T

arXiv:2609.11188v1 Announce Type: new Abstract: Synthetic image attribution (SIA) has become increasingly important with the rapid advancement of text-to-image generation models. However, accurately i

arXiv:2609.10729v1 Announce Type: cross Abstract: Quantum-inspired classical algorithms have dequantized several quantum machine learning routines by replacing quantum linear-algebra subroutines with

arXiv:2609.11299v1 Announce Type: cross Abstract: We propose an all-reflective two-mirror projection system for extreme ultraviolet (EUV) lithography operating at exposure wavelengths of 13.5~nm (Mo/S

arXiv:2609.10983v1 Announce Type: cross Abstract: Stress localization in heterogeneous solids is governed by the bimaterial interface, where the displacement field remains C^0-continuous, while in-pla