Knowledge catalogue
arXiv:2609.09299v1 Announce Type: new Abstract: Decision trees are prized for their interpretability and strong performance on tabular data, but popular greedy top-down induction algorithms can yield
arXiv:2601.17036v2 Announce Type: replace-cross Abstract: ArXiv recently prohibited the upload of unpublished review papers to its servers in the Computer Science domain, citing a high prevalence of L
arXiv:2602.19600v2 Announce Type: replace-cross Abstract: Many high-dimensional datasets concentrate near a low-dimensional structure embedded in the ambient space. Generative models for such data mus
arXiv:2609.07598v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly shape communication, learning, work, creativity, and decision-making, yet social-science research on these d
May, damn it, not six weeks. Senior, not entry level. Jacob was a senior researcher who joined Anthropic in May. My Anthropic colleagues and I had been trying to recruit him for ~2 years, because we k
arXiv:2609.09907v1 Announce Type: new Abstract: Meta-learning has emerged as an effective paradigm for transferring knowledge across sequential bandit tasks. While substantial progress has been made f
arXiv:2609.10433v1 Announce Type: cross Abstract: This study develops a deep reinforcement learning framework for training Unmanned Aerial Vehicle (UAV) agents to navigate and monitor simulated wildfi
arXiv:2512.10237v2 Announce Type: replace Abstract: Reinforcement Learning from Human Feedback has emerged as a standard for aligning diffusion models. However, we identify a fundamental limitation in
arXiv:2609.07663v1 Announce Type: cross Abstract: A wrong number is worse than no answer. Across factuality-critical domains -- audience metrics, scheduling and rights in media; dosages and lab values
not counting Sam himself who is frequently in DC OpenAI employs FIVE lobbying firms and has over 100 staffers in their Washington, DC office. They must push for AI legislation to justify their existen
arXiv:2609.10336v1 Announce Type: new Abstract: Despite significant progress in odometry estimation, long-term drift remains a fundamental limitation of incremental pose integration, especially in lar
arXiv:2609.10321v1 Announce Type: new Abstract: Knowledge distillation offers an efficient route to transfer a task-adapted vision-language teacher to a compact student. The training target in current
OpenAI hid the details of the wiki incident from the investigators of the later HuggingFace hack. When caught, they responded only with corporate BS. This cover-up of unprecedentedly misaligned behavi
arXiv:2609.09981v1 Announce Type: cross Abstract: We study offline inference for the optimal value in reinforcement learning. Two new nuisances are derived as fixed points of a self-induced Bellman eq
arXiv:2203.06158v3 Announce Type: replace Abstract: Scheduled batch jobs are widely used on asynchronous computing platforms to execute enterprise applications such as promotional notifications and ca
arXiv:2609.10198v1 Announce Type: new Abstract: Emotions are a pervasive feature of political communication, yet existing research has focused primarily on describing patterns of emotional expression
arXiv:2603.22714v2 Announce Type: replace-cross Abstract: We present PopResume, a population-representative resume dataset for causal fairness auditing of LLM- and VLM-based resume screening systems.
Maxwell Zeff / Wired: Q&A with AI researcher Jacob Coxon, who quit Anthropic, on the need for industry-wide, international coordination to limit recursive self-improvement, and more — Jacob Coxon talk
arXiv:2609.07901v1 Announce Type: new Abstract: Weight quantization largely determines the economics of serving open-weight LLMs. Its costs are usually assessed with capability benchmarks, on which 4-
arXiv:2609.10021v1 Announce Type: new Abstract: Vision--language--action (VLA) models acquire broad generalization through large-scale pretraining, yet adapting them to a new task and robot embodiment
arXiv:2609.07255v1 Announce Type: new Abstract: Language-model agents increasingly rely on skills: reusable procedural knowledge for reasoning, tool use, and interaction. Existing work studies how ski
arXiv:2609.05800v1 Announce Type: new Abstract: Activation steering controls LLM behavior at inference time by adding learned directions to hidden states, but existing methods handle one concept at a
arXiv:2609.06540v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in safety-critical applications, yet jailbreak attacks can conceal harmful intent through role-
arXiv:2609.08452v1 Announce Type: new Abstract: Multi-agent large language models solve complex tasks by coordinating several policies in a shared environment. However, existing reinforcement learning
arXiv:2609.09899v1 Announce Type: cross Abstract: Language models can fluently describe how they would behave: whether they would cave to pushback, misuse a tool, or lie under pressure. Is that descri
arXiv:2609.09719v1 Announce Type: new Abstract: Text-aligned speech tokenization methods have emerged to better align speech tokens with LLM token spaces, enabling more effective utilization of pretra
arXiv:2609.09890v1 Announce Type: new Abstract: Multi-view diffusion models have shown strong performance in scenes with strong geometric priors and sparse semantics, such as indoor rooms or simple ou
arXiv:2509.24877v3 Announce Type: replace Abstract: The social science of large language models (LLMs) examines how these systems evoke mind attributions, interact with one another, and transform huma
arXiv:2609.07713v1 Announce Type: new Abstract: Generative and agentic AI are reshaping both the production and evaluation of scientific research. These developments are often studied separately, as q
arXiv:2609.10296v1 Announce Type: new Abstract: Non-invasive speech decoding remains constrained by the low signal-to-noise ratio of neural recordings, which makes fine-grained reconstruction of phone
this was wild amounts of disinformation / fear mongering / the stupidest interview ive ever seen: 1) ai did NOT hack huggingface on its own 'independent volition'. it wasnt sitting there thinking hmm
arXiv:2609.09925v1 Announce Type: cross Abstract: Modern vision-language-action (VLA) policies predict a whole chunk of actions: one to two seconds of coordinated motion emitted in a single forward pa
Tomorrow I will rip Jacob Coxon’s CNN appearance. But let’s cut with the six weeks/entry level bullshit and the character assassination. My best source (and one I have a lot of faith) in is that he st
arXiv:2603.15576v2 Announce Type: replace Abstract: This paper develops new variance-reduction techniques for the forward-reflected-backward splitting (FRBS) method to solve a class of possibly nonmon
arXiv:2609.06816v1 Announce Type: new Abstract: Decision-time search in perfect and imperfect information games with enumerable belief states are effective methods for game AI. Collectible card games
arXiv:2609.10224v1 Announce Type: new Abstract: Vision-language models such as CLIP embed images and text in a shared space, where modality-specific distributions often remain separated. Existing acco
arXiv:2609.09300v1 Announce Type: new Abstract: Video understanding demands a convergence of complementary capabilities across perception, temporal understanding, and complex reasoning, which are diff
arXiv:2603.25021v3 Announce Type: replace Abstract: Existing Multimodal Large Language Models (MLLMs) often suffer from hallucinations in long video understanding (LVU), primarily due to the imbalance
arXiv:2609.06840v1 Announce Type: cross Abstract: Web Application Firewalls (WAFs) mainly rely on signatures to detect known attacks, which can leave gaps against modified or previously unseen payload
arXiv:2609.10261v1 Announce Type: new Abstract: Multi-modal medical image segmentation leverages complementary diagnostic information, yet fusion can underperform single-modality baselines when spatia
arXiv:2609.05871v1 Announce Type: cross Abstract: Audio-conditioned language models often underuse acoustic cues such as prosody, emotion, and non-speech sounds, raising the question of whether ASR-su
arXiv:2510.15047v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) as agents often fail to improve in new environments. We identify and characterize a failure mode we call explorat
Why the public needs to step up. I talk with @CBCNews about why a (temporary) boycott of generative AI, as unlikely as it is, ought to be on the table. https://youtu.be/3BBp-tCvsOM?si=88KxNluVZnuzRw3L
arXiv:2609.09677v1 Announce Type: new Abstract: Incremental-text streaming text-to-speech (TTS) needs online text progress tracking for synchronized highlighting, interruption handling, and dialogue-h
arXiv:2609.08672v1 Announce Type: cross Abstract: Streaming automatic speech recognition (ASR) for real-time voice agents and full-duplex dialogue must provide accurate partial transcripts with low co
arXiv:2609.09388v1 Announce Type: new Abstract: Brain-age prediction models are commonly evaluated by predictive accuracy, yet accurate predictions alone do not establish that a model relies on reprod
arXiv:2609.07784v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for everyday assistance, yet existing benchmarks only partially reflect the requests users naturally
arXiv:2609.08247v1 Announce Type: new Abstract: Wallet reputation scores decide who receives an airdrop, who can borrow, and who enters an allowlist across decentralised finance. They almost always be
arXiv:2609.08211v1 Announce Type: cross Abstract: Real-world Multi-Objective Reinforcement Learning (MORL) often suffers from sparse rewards, reward conflicts, and late-stage reward tug-of-war, causin
arXiv:2609.08826v1 Announce Type: cross Abstract: When an external reference set (an anchor) is used to decompose an LLM-judge panel's error into a quality signal and a shared common-mode error, stand
arXiv:2609.05895v1 Announce Type: new Abstract: We study a finite-horizon online resource allocation problem with initial resource capacities proportional to the horizon. In each period, a request typ
arXiv:2506.12809v2 Announce Type: replace Abstract: The long horizon forecasting (LHF) problem has come up in the time series literature for over the last 35 years or so. This review covers aspects of
A significant fraction of humanity read this thread. Is anyone prepared to do something about it? Fretting doesn’t count. I resigned from Anthropic today. I spent the last three years doing pretrainin
arXiv:2609.07974v1 Announce Type: cross Abstract: Fairness in clustering has attracted sustained research interest, motivated by the need to ensure equitable representation of protected groups in mach
arXiv:2505.02627v2 Announce Type: replace Abstract: Compositional generalizationnicode{x2013}the ability to systematically process novel combinations of known componentsnicode{x2013}is a hallmark of h
arXiv:2609.06460v1 Announce Type: new Abstract: Recently, Masked Pretraining (MPT) based on reconstruction pretraining tasks has risen to a promising self-supervised learning paradigm across various d
arXiv:2609.07821v1 Announce Type: cross Abstract: Chain-of-Thought (CoT) improves the reasoning ability of Large Language Models (LLMs) but incurs substantial computation and context costs. Existing m
arXiv:2603.18074v2 Announce Type: replace Abstract: Technical-service LLM agents are entering production workflows, where value depends on whether engineers adopt generated replies. Service tickets hi
arXiv:2609.08788v1 Announce Type: new Abstract: Dense self-attention treats all token pairs as equally plausible before learning, an interaction-isotropic prior that can be mismatched to structured si
arXiv:2406.04314v4 Announce Type: replace Abstract: Generating visually appealing images is fundamental to modern text-to-image generation models. A potential solution to better aesthetics is direct p