Inference-Time Nash Alignment
arXiv:2609.08082v1 Announce Type: new Abstract: Preference-based fine-tuning methods such as RLHF and DPO require substantial compute and large preference datasets. They also need direct access to the
Knowledge catalogue
arXiv:2609.08082v1 Announce Type: new Abstract: Preference-based fine-tuning methods such as RLHF and DPO require substantial compute and large preference datasets. They also need direct access to the
arXiv:2502.00858v4 Announce Type: replace Abstract: Natural-language instructions rarely specify every detail required for embodied action. An agent asked to ``prepare an apple,'' for example, must st
arXiv:2410.03315v2 Announce Type: replace Abstract: Federated learning (FL) is a machine learning paradigm where clients with different behaviors and preferences can learn collaboratively without comp
arXiv:1503.01967v3 Announce Type: replace-cross Abstract: According to E.T. Jaynes and E.P. Wigner, entropy is an anthropomorphic concept in the sense that in a physical system correspond many thermod
arXiv:2609.09482v1 Announce Type: new Abstract: Critical infrastructure location data is often incomplete and unevenly distributed globally, especially in developing regions. Earth observation foundat
arXiv:2609.09821v1 Announce Type: cross Abstract: Physics-based character control is a long-standing challenge in computer graphics and robotics, requiring policies that satisfy complex dynamics while
arXiv:2512.11273v3 Announce Type: replace-cross Abstract: Multi-period portfolio optimization is important for real portfolio management, as it accounts for transaction costs, path-dependent risks, an
arXiv:2609.09185v1 Announce Type: new Abstract: Multi-label chest X-ray classification has attracted considerable attention in recent years, with the effective use of visual representations and clinic
arXiv:2609.05975v1 Announce Type: cross Abstract: We introduce Chain of Intent, a governance framework for agentic AI at small regulated firms, and validate it against a failure it was built to addres
arXiv:2609.05764v1 Announce Type: cross Abstract: The key-value (KV) cache is the dominant memory bottleneck in long-context large language model (LLM) decoding: every step reads it entirely, so decod
arXiv:2609.09909v1 Announce Type: new Abstract: Although text-to-image diffusion models generally exhibit strong prompt-following ability, we identify a persistent and previously underexplored failure
Kenneth Chang / New York Times: Interview with mathematician Tristan Buckmaster on being drawn into the OpenAI-Anthropic fight; OpenAI says it made progress on another Millennium Prize problem — Trist
🚀 Introducing DeepSeek-V4.1-Flash: smarter, faster, more efficient. 🔹 Introducing the smallest model in our new architecture family, with native visual understanding. 🔹 Designed for greater capability
Introducing Gen-1 Slides: an open model that matches Claude Opus 5 on slide generation, at ~1/17 of its input-token price. @genspark_ai post-trained it from a @MiniMax_AI M3 base with Fireworks Lab us
introducing preemptible compute for together gpu clusters same nvidia gpu infrastructure, 50% of the on-demand price built for evals, fine-tuning, batch inference + short experiments, with up to 5 min
Agent skills fit well alongside documentation and remote MCP servers as ways of enabling the success of your AI workflows. They reduce context window usage for certain use cases, and they're straightf
arXiv:2609.10292v1 Announce Type: new Abstract: Data augmentation is fundamental to training modern deep vision and multimodal models. While individual methods, such as RandAug, CutMix, Mixup, RandEra
arXiv:2609.09022v1 Announce Type: cross Abstract: AI-assisted programming raises distinct questions about who produces code, who feels ownership of it, and who is responsible when it fails. This resea
arXiv:2609.06250v1 Announce Type: cross Abstract: Security Operations Centers (SOCs) process large amounts of tickets, most of which are low-interest events not worthy of further investigation. The re
arXiv:2609.08772v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly being investigated for physiological time-series prediction, yet their effectiveness may depend not only o
It's time to call these end-of-the-world anti-AI messaging groups exactly what they are: Terror cells - They funnel and wash money from a few donors to smaller groups to obscure origin - insert sleepe
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 knew he was a strong researcher at OpenAI. Before he le
arXiv:2609.09630v1 Announce Type: new Abstract: Standard behavior cloning supervises actions without explicitly constraining the future representation paired with each demonstrated action chunk. We in
Identity and access management company JumpCloud Inc. today extended its Agentic IAM service to give information technology teams direct control over the autonomous artificial intelligence agents runn
arXiv:2609.09698v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) have achieved remarkable success across diverse applications, yet they remain highly vulnerable to adversarial attacks that
arXiv:2609.10144v1 Announce Type: cross Abstract: AI systems become more useful when they can adapt to the people using them, but in multi-agent systems, useful context learned by one agent often rema
arXiv:2609.08173v1 Announce Type: new Abstract: Sparse autoencoder (SAE)-based steering has been widely used to address knowledge conflicts by guiding LLMs to be more faithful to the contextual knowle
arXiv:2602.02846v2 Announce Type: replace Abstract: Sampling-based motion planners (SBMPs) are widely used for robot motion planning with complex kinodynamic constraints in high-dimensional spaces, ye
arXiv:2512.05461v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are rapidly being integrated into computational social science research, yet their blackboxed training and design
arXiv:2609.10266v1 Announce Type: new Abstract: LLM serving systems already reuse KV caches, but only when the reused text sits at the very start of the prompt. Two growing workloads break this condit
arXiv:2609.07309v1 Announce Type: cross Abstract: Robustness evaluation of large language models (LLMs) remains a critical challenge, particularly in assessing their sensitivity to perturbations in in
arXiv:2508.05427v2 Announce Type: replace Abstract: Large language models (LLMs) are beginning to reshape how organic-synthesis workflows are represented, queried, planned, and connected to experiment
arXiv:2609.07594v1 Announce Type: cross Abstract: Conversational Task Assistants (CTAs) are multimodal dialogue systems that support users in complex real-world tasks such as cooking and DIY through v
arXiv:2606.13945v2 Announce Type: replace Abstract: Rare diseases affect over 300 million patients across more than 7{,}000 conditions, yet no single hospital encounters enough cases of any one condit
arXiv:2609.09827v1 Announce Type: new Abstract: This work introduces a family of tunable lifting schemes for biorthogonal wavelet filter banks. We propose three lifting strategies: low-pass tuning (LS
arXiv:2609.05834v1 Announce Type: new Abstract: World models promise a general route to embodied intelligence: learn predictive dynamics once, then reason, plan, and act with them. Increasingly, the r
arXiv:2609.09491v1 Announce Type: new Abstract: Camera pose estimation is a key step in 3D reconstruction and view-synthesis pipelines. We present a deep, global Structure-from-Motion framework based
arXiv:2609.10286v1 Announce Type: new Abstract: Humanoid locomotion on granular terrain remains a significant challenge due to its complex foot-terrain interaction dynamics that are difficult to model
arXiv:2609.10333v1 Announce Type: new Abstract: Uncertainty estimation for medical vision--language models (VLMs) using conformal prediction has gained increasing attention due to its distribution-fre
arXiv:2609.09234v1 Announce Type: cross Abstract: Vision-guided reinforcement learning for Unmanned Aerial Vehicles (UAVs) remains challenging due to unstable policy optimisation, aggressive explorati
arXiv:2609.06849v1 Announce Type: new Abstract: Sleep provides a nightly window into health by capturing coordinated activity across the brain, heart, muscles and respiratory system. We introduce Slee
arXiv:2609.10490v1 Announce Type: new Abstract: This feature article provides an overview of the theoretical foundations for coVariance neural networks (VNNs), i.e., graph neural networks (GNNs) opera
arXiv:2609.09572v1 Announce Type: cross Abstract: Synthetic data has become a promising way to scale model training beyond limited human-generated data but it may also induce strong model collapse (Do
arXiv:2609.08288v1 Announce Type: new Abstract: Travel survey data are essential for transportation planning and travel behavior analysis, yet collecting large-scale representative samples is costly a
arXiv:2609.09477v1 Announce Type: new Abstract: Delineating lung tumours on computed tomography (CT) takes a considerable share of the time spent on radiotherapy planning, and a contour proposed by a
arXiv:2609.09188v1 Announce Type: new Abstract: Lensless near-eye sensing is often described as privacy-friendly because its coded measurements are visually unintelligible. Yet visual unintelligibilit
arXiv:2609.08180v1 Announce Type: new Abstract: Retrieval-augmented personalization enables large language models to produce more accurate and preference-aligned outputs using relevant records retriev
Axios: Letter: the Senate disaster management subcommittee, led by Sen. Josh Hawley, is probing OpenAI's handling of the Hugging Face breach, calling it “reckless” — A Republican-led Senate subcommitt
arXiv:2609.09889v1 Announce Type: new Abstract: Automatic Speech Recognition (ASR) technology is fundamental to customer service automation and large-scale transcription. However, even advanced ASR mo
arXiv:2609.09634v1 Announce Type: new Abstract: Large networks and ensembles often lead medical image segmentation challenges, but their storage and inference demands complicate deployment. We present
arXiv:2609.10534v1 Announce Type: cross Abstract: We present a simple decomposition of a neural-network-based normalizing flow that naturally uncovers a pivotal statistic (or something close) in the p
arXiv:2607.14112v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are trained and evaluated as though perfect reliability is achievable for any task given sufficient scale. We sho
arXiv:2609.10095v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) enables real-time novel view synthesis but produces millions of primitives through adaptive densification, leading to signi
arXiv:2609.10239v1 Announce Type: cross Abstract: Graph-based retrieval can improve multi-hop question answering, but existing approaches often incur high query-time costs and produce diffuse, oversiz
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:2609.08049v1 Announce Type: cross Abstract: Large language models (LLMs) are rapidly emerging as a new paradigm for modeling social networks by representing users and their relationships and int
arXiv:2511.12563v2 Announce Type: replace Abstract: Modeling the dynamics of financial Limit Order Books (LOB) at the message level is challenging due to irregular event timing, rapid regime shifts, a
I’ve been working on perfecting my setup ever since 3.8 hit, but no longer pay for subscriptions. I had a coding interview today and setup openrouter ahead of time as another option. I figured I could
arXiv:2602.00276v3 Announce Type: replace Abstract: Large language models (LLMs) have demonstrated strong reasoning capabilities on math and coding, but frequently fail on symbolic classical planning