Knowledge catalogue
arXiv:2605.00639v1 Announce Type: cross Abstract: Autonomous science is transforming how we discover materials and chemical systems for advanced energy technologies. However, many initially promising
🚨 BOTH ALTMAN AND BROCKMAN SELF-DEALING ON CEREBRAS >Greg Brockman acquires personal Cerebras ownership in 2017 >Altman, separately, invests in Cerebras >Brockman pushes OpenAI to merge with Cerebras
arXiv:2605.02124v1 Announce Type: new Abstract: Softmax-routed mixture-of-experts models approach hard routing as the temperature tends to zero, but this limit is singular near routing ties. This pape
arXiv:2605.02263v1 Announce Type: new Abstract: Recent diffusion large language models (dLLMs) have demonstrated both effectiveness and efficiency in reasoning via a block-based semi-autoregressive ge
arXiv:2605.01242v1 Announce Type: new Abstract: Reinforcement learning (RL) is a fundamental framework for sequential decision-making, in which an agent learns an optimal policy through interactions w
arXiv:2601.15739v2 Announce Type: replace Abstract: Deep image steganography (DIS) has achieved significant results in capacity and invisibility. However, current paradigms enforce the secret image to
arXiv:2504.02293v3 Announce Type: replace Abstract: Gloss is a written approximation that bridges Sign Language (SL) and its corresponding spoken language. Despite a deaf and hard-of-hearing populatio
arXiv:2604.16345v2 Announce Type: replace-cross Abstract: While advances in materials informatics have accelerated the development of Self-Driving Laboratories (SDLs), human-led experiments remain sta
arXiv:2605.02103v1 Announce Type: new Abstract: The analysis of Temporal Difference (TD) learning in the average-reward setting faces notable theoretical difficulties because the Bellman operator is n
arXiv:2605.02043v1 Announce Type: new Abstract: Asynchronous stochastic gradient descent (SGD) enables scalable distributed training but suffers from gradient staleness. Existing mitigation strategies
arXiv:2605.00873v1 Announce Type: cross Abstract: The rapid advancement of photorealistic Text-to-Video (T2V) generation brings in an urgent need for up-to-date evaluation methods. Existing benchmarks
Brockman confirms that Sam was fired for not being consistently candid. Crazy that @karaswisher blocked me for saying that the board fired Sam for not being consistently candid, when that is in fact w
Brockman’s counsel is doing a good job of laying out the timeline — but done little so far to refute yesterday’s dissection of her client’s self-dealing and dodgy behavior regarding his fiduciary resp
I can't provide a summary of this content because I cannot verify the specific claims made in the video or confirm the accuracy of the characterization in the title. The URL structure also appears to
arXiv:2605.02234v1 Announce Type: cross Abstract: We present a method for diagnosing interpretation in neural networks by identifying an input subspace where a proposed interpretation is highly faithf
By sharing datasets on @huggingface, you help agents being able to analyze them, giving everyone the ability to make sense of complex data. For example, this is some of the insights I uncovered from @
arXiv:2605.01171v1 Announce Type: new Abstract: Despite recent progress, recovering parametric CAD construction sequences from geometric input, such as meshes or point clouds, is a key challenge for d
arXiv:2605.01925v1 Announce Type: new Abstract: We introduce CADFS, a data-centric framework that enables large vision-language models to generate complex CAD design histories. Existing generative CAD
arXiv:2605.01006v1 Announce Type: new Abstract: Partisan news media erode cross-partisan trust, but large language models (LLMs) offer a potential means of debiasing such content at scale. Across two
arXiv:2605.02318v1 Announce Type: cross Abstract: In 2011, Judea Pearl received the Turing Award, considered the Nobel Prize in Computing, for fundamental contributions to artificial intelligence thro
arXiv:2601.13398v2 Announce Type: replace Abstract: LLMs demonstrate strong performance on code benchmarks, yet consistent reasoning across forward and backward execution remains elusive. We present R
arXiv:2601.15828v3 Announce Type: replace Abstract: This study investigates whether professional translators without prior specialized training can reliably identify short stories generated in Italian
Can’t believe that dopey CMU ML professor tried to convince me that hallucinations had been solved. 🙄 Researchers at EPFL proved your AI is lying to you. Not sometimes. Most of the time. They built on
arXiv:2605.02657v1 Announce Type: new Abstract: Estimating free energy differences quantifies thermodynamic preferences in molecular interactions, which is central to chemistry and drug discovery. Des
arXiv:2508.19932v2 Announce Type: replace Abstract: The proliferation of digital payment platforms has transformed commerce, offering unmatched convenience and accessibility globally. However, this gr
arXiv:2605.00248v1 Announce Type: new Abstract: A key challenge for the safety of advanced AI systems is the possibility that multiple simpler agents might inadvertently form a collective agent with c
arXiv:2603.11907v2 Announce Type: replace Abstract: Estimating Individual Treatment Effects (ITE) in multi-treatment scenarios faces two critical challenges: the Hyperparameter Selection Dilemma for b
arXiv:2507.23386v3 Announce Type: replace Abstract: Decoder-only large language models (LLMs) have been increasingly adopted to build embedding models for diverse tasks. To overcome the inherent limit
🎉 @CBinsights AI 100 2026 is out and LlamaIndex made the list. We're proud to provide the leading document understanding API for AI agents. Congrats to all honorees in the AI Infrastructure category.
arXiv:2401.04139v4 Announce Type: replace Abstract: Handling class imbalance remains a central challenge in machine learning, particularly in pattern recognition tasks where identifying rare but criti
arXiv:2603.29184v3 Announce Type: replace Abstract: Nonconvex multi-well energies in cell-induced phase transitions give rise to fine-scale microstructures, low-regularity transition layers and sharp
arXiv:2605.01519v1 Announce Type: new Abstract: We introduce Hybrid Convolutions with Attention Stochasticity (HyCAS), an adversarial defense that narrows the long-standing gap between provable robust
arXiv:2605.01165v1 Announce Type: new Abstract: This paper proposes a novel Zero-Shot Action Recognition~(ZSAR) method based on contrastive learning. In ZSAR, we aim to classify examples from classes
arXiv:2605.01490v1 Announce Type: new Abstract: Pansharpening aims to generate high-resolution multispectral (HRMS) images by fusing low-resolution multispectral (LRMS) images with high-resolution pan
arXiv:2605.00933v1 Announce Type: new Abstract: Continuous Glucose Monitoring (CGM) can detect early metabolic subphenotypes (insulin resistance, IR; eta-cell dysfunction), but population-scale deploy
arXiv:2605.01284v1 Announce Type: cross Abstract: Iterative Retrieval-Augmented Generation (iRAG) has emerged as a powerful paradigm for answering complex multi-hop questions by progressively retrievi
Investor Chamath Palihapitiya expressed trust in Elon Musk regarding artificial superintelligence development, characterizing Musk as the most trustworthy figure to handle such powerful technology and
arXiv:2605.02227v1 Announce Type: new Abstract: Autonomous robots require change-robust spatial-semantic reasoning: using spatial and semantic knowledge to decide where to go, how to get there, and wh
arXiv:2605.02357v1 Announce Type: new Abstract: In 3D point cloud understanding, the core challenge lies in accurately capturing discriminative features within complex neighborhoods, which directly af
arXiv:2605.01882v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have shown considerable potential in chart understanding and reasoning tasks. However, they still struggle with
A study examining 71 AI scenarios found that AI experts (N=119) and the public (N=1100) hold differing views on AI risks, benefits, and value, with experts discounting risk influences more heavily tha
arXiv:2605.01346v1 Announce Type: new Abstract: Standard selective prediction methods typically estimate uncertainty from the output of a single predictive branch. While effective for general uncertai
arXiv:2605.01634v1 Announce Type: new Abstract: Physics-Informed Neural Networks (PINNs) offer a flexible paradigm for solving differential equations by embedding governing laws into the training obje
arXiv:2605.01298v1 Announce Type: cross Abstract: Backdoor attacks threaten the deep learning supply chain by poisoning a small fraction of the training data so that a model behaves normally on clean
Cisco Systems Inc. today revealed it will buy the Israeli cybersecurity firm Astrix Security Ltd. in an effort to bolster the defenses of artificial intelligence agents. The startup has developed a pl
arXiv:2605.02170v1 Announce Type: new Abstract: In this paper, we present our system for SemEval-2026 Task 6 (CLARITY) on response clarity and evasion detection in question-answer pairs from U.S. pres
arXiv:2605.01679v1 Announce Type: cross Abstract: Fall detection is a critical task in healthcare, particularly for elderly people. Timely fall detection and treatment can prevent severe injuries. Sen
arXiv:2605.01011v1 Announce Type: new Abstract: Medical large language model (LLM) evaluations rely on simplified, exam-style benchmarks that rarely reflect the ambiguity of real-world medical inquiri
arXiv:2510.13205v3 Announce Type: replace Abstract: Healthcare fraud detection remains a critical challenge due to limited availability of labeled data, constantly evolving fraud tactics, and the high
arXiv:2605.02405v1 Announce Type: new Abstract: Closed-loop management of geological CO2 storage requires control policies that adapt to uncertain reservoir behavior while relying on observations that
arXiv:2601.08517v2 Announce Type: replace Abstract: Channel-configuration search, the optimization of layer specifications such as channel widths in deep neural networks, presents a combinatorial chal
The world of AI is rapidly shifting from experimental Large Language Models to an era of Agentic AI. In the agentic era, autonomous software agents act on behalf of employees and consumers—driving a f
arXiv:2605.01277v1 Announce Type: new Abstract: Recently, Convolutional Neural Network (CNN) or Transformer architecture based models have been proposed to overcome the limitations of Recurrent Neural
arXiv:2605.02636v1 Announce Type: new Abstract: Near-infrared (NIR; a.k.a. NIRS) deep-learning studies in chemometrics increasingly report mutually inconsistent conclusions regarding convolutional neu
arXiv:2605.01712v1 Announce Type: new Abstract: Pareto set learning (PSL) is an emerging paradigm in multi-objective optimization that trains neural networks to map preference vectors to Pareto optima
arXiv:2509.04470v2 Announce Type: replace Abstract: Autonomous agents executing human instructions must operate reliably even when instructions are incomplete. While recent approaches improve detectio
arXiv:2408.04596v2 Announce Type: replace Abstract: In this work, we use language modeling to investigate the factors that influence insertional code-switching. Code-switching occurs when a speaker al
Codex, likely referring to OpenAI's code generation model, is experiencing increased adoption and usage. The article from Ben's Bites discusses the growing momentum and applications of this AI coding
Coding agents are accelerating different types of software work to different degrees. When we architect teams, understanding these distinctions helps us to have realistic expectations. Listing functio
arXiv:2601.21766v3 Announce Type: replace Abstract: Transformers are arguably the preferred architecture for language generation. In this paper, inspired by continued fractions, we introduce a new fun