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arXiv:2604.07813v2 Announce Type: replace Abstract: Learning theories have historically changed when the conditions of learning evolved. Generative and agentic AI create a new condition by allowing le

arXiv:2601.17261v4 Announce Type: replace Abstract: Zeroth-Order (ZO) optimization has emerged as a promising solution for fine-tuning LLMs under strict memory constraints, as it avoids the prohibitiv

arXiv:2605.23459v1 Announce Type: cross Abstract: Enterprise AI systems, built on large language models, retrieval pipelines and autonomous agents, introduce a class of risks that traditional software

arXiv:2604.03244v2 Announce Type: replace Abstract: This position paper argues that standardized item-level benchmark data should become the default infrastructure for AI evaluation. Current evaluatio

arXiv:2605.22923v1 Announce Type: cross Abstract: Large language models can answer questions about textbooks, lecture notes, and programming exercises more reliably when their answers are grounded in

arXiv:2605.23448v1 Announce Type: cross Abstract: This work examines an imbalance in artificial intelligence (AI) security research: the field tends to produce more work on attacking AI systems than o

arXiv:2602.05472v2 Announce Type: replace Abstract: The quest for expert-level reasoning in Large Language Models (LLMs) has been hampered by a persistent extit{reward bottleneck}: traditional reinfor

Amo Dei appears to be a project or concept shared by Emad Mostaque, the CEO of Stability AI, on X (formerly Twitter). Without access to the specific post content, this likely relates to either a techn

arXiv:2601.22367v2 Announce Type: replace-cross Abstract: Generalized Bayesian Inference (GBI) tempers a loss with a temperature eta > 0 to mitigate overconfidence and improve robustness under model m

arXiv:2605.22824v1 Announce Type: cross Abstract: Environmental monitoring is a crucial component of the smart city infrastructure. It enables informed decision making which enhances sustainability, p

An open source model has returned to #1 on the 3D Design leaderboard by Design Arena. Kimi K2.6 has reached the top of the leaderboard for 3D Design, ahead of models 10X more expensive like Opus 4.7 b

arXiv:2605.23417v1 Announce Type: new Abstract: Most black-box optimization methods require extensive hyperparameter tuning, often limiting their ability to generalize across different optimization do

arXiv:2603.17879v2 Announce Type: replace-cross Abstract: This work presents a multi-label temporal event detection framework for video capsule endoscopy (VCE) that addresses the extreme class imbalan

Ollama Talk is an Android app that connects to an Ollama server, enabling conversations with AI models like Llama and Mistral . The app features an intuitive chat interface with real-time conversation

Anthropic is really a mixed bag; they rightly support moderate regulation, but they invite wildly anthropomorphic language about LLMs, and steal IP just like their peers. Anthropic are the bad guys. W

arXiv:2605.23156v1 Announce Type: new Abstract: Several machine learning models are defined for inputs of any size, such as graphs with different numbers of nodes and point clouds containing varying n

arXiv:2605.23733v1 Announce Type: cross Abstract: Whole-body tracking (WBT) models have become a key foundation for humanoid robots, enabling them to imitate diverse motions with high fidelity. Traini

arXiv:2605.23061v1 Announce Type: cross Abstract: Standard neural network training relies on learning-rate schedules tied to a fixed horizon, leading to strong path dependence and costly re-tuning as

This post discusses workarounds for content restrictions in Stable Diffusion, specifically showcasing examples of using the Director feature with LTX 2.3 model and alternative techniques to generate c

arXiv:2605.23751v1 Announce Type: new Abstract: We revisit the I/O complexity of attention in large language models. Given query-key-value matrices Q,K,VinR^{nimes d}, and a machine with fast memory s

arXiv:2605.22871v1 Announce Type: cross Abstract: Machine unlearning is a fundamental mechanism that enforces the right to be forgotten. Existing unlearning studies that rely on label manipulation or

arXiv:2605.23325v1 Announce Type: new Abstract: Social media has become a crucial arena for shaping public narratives during armed conflicts, providing space for both harmful and constructive communic

arXiv:2605.23134v1 Announce Type: new Abstract: No existing nested Archimedean copula tool handles all three of (a) arbitrary per-variable (right-)censoring in survival analysis, (b) arbitrary nesting

arXiv:2602.07235v2 Announce Type: replace-cross Abstract: Watermarking is an important tool for promoting the responsible use of large language models (LLMs). Existing watermarks insert a signal into

arXiv:2605.23243v1 Announce Type: cross Abstract: We evaluate whether frontier LLMs are ready for cybersecurity through a dual-mode benchmark: white-box function-level vulnerability detection (VulnLLM

arXiv:2509.06896v2 Announce Type: replace Abstract: Targeted data poisoning attacks manipulate model predictions on specific test samples by injecting malicious data into training. Yet existing evalua

arXiv:2605.23454v1 Announce Type: new Abstract: Rubric-based rewards offer a promising way to extend reinforcement learning (RL) for large language models beyond tasks with automatically verifiable an

arXiv:2605.23562v1 Announce Type: cross Abstract: Sparse rewards are a major bottleneck in multi-agent reinforcement learning (MARL), where simultaneous learning induces non-stationarity and makes rew

arXiv:2605.23416v1 Announce Type: new Abstract: Acoustic vowel dynamics have some speaker-identifying characteristics, which have been ascribed to individual properties of articulatory strategies: for

As one of the first people to warn about a possible AI backlash—years ago—let me tell you this: it’s going to get much, much worse. It breaks my heart that AI—something I spent my whole life thinking

As enterprises confront spiraling cloud inference bills, on-prem AI computing is emerging as the decisive lever for making agentic AI economically viable at scale. Dell Technologies Inc.’s announcemen

arXiv:2605.23147v1 Announce Type: cross Abstract: Role prompts of the form As X, do Y admit a clean linear decomposition at one specific site in the residual stream: the prompt-to-answer transition --

Grok, an AI assistant developed by xAI, was asked about its prime directive, and apparently provided an elegant response that impressed Elon Musk enough to share on X. The post suggests Grok's answer

arXiv:2605.23497v1 Announce Type: new Abstract: Large language models are increasingly used for legal research, yet their fixed training cutoffs and reliance on static parametric knowledge are at odds

arXiv:2605.23234v1 Announce Type: new Abstract: Assessing the spatial fairness of predictive models involves establishing whether they are statistically penalizing (favoring) individuals associated wi

arXiv:2605.23591v1 Announce Type: cross Abstract: We introduce a model for neural scaling laws under sparse activations. In the model, test loss is often dominated by rare coordinates that are never o

arXiv:2605.22133v2 Announce Type: replace-cross Abstract: Recent advances in generative modeling show that pretrained representations can improve generation as conditioning features or alignment targe

arXiv:2605.23473v1 Announce Type: cross Abstract: Bayesian optimization is widely employed for optimizing complex black-box functions but struggles with the curse of dimensionality. Random embedding,

arXiv:2601.22324v2 Announce Type: replace Abstract: Modern clinical practice relies on evidence-based guidelines implemented as compact scoring systems composed of a small number of interpretable deci

arXiv:2605.23165v1 Announce Type: cross Abstract: Autonomous robotic exploration of unknown and hazardous environments, a long-standing challenge, can be significantly improved by leveraging the advan

arXiv:2605.23204v1 Announce Type: new Abstract: Scientific research is being reshaped by AI systems that move beyond isolated assistance toward longer-horizon workflows spanning literature grounding,

arXiv:2510.12787v4 Announce Type: replace Abstract: We present Ax-Prover, a multi-agent system for automated theorem proving in Lean that can solve problems across diverse scientific domains and opera

arXiv:2605.23500v1 Announce Type: new Abstract: Segmentation is a fundamental task in computer vision, underpinning pixel-level scene understanding and serving as a cornerstone for applications rangin

b9310 is a release build of llama.cpp, a C/C++ implementation for LLM inference . As an intermediate build number in the llama.cpp project's continuous release cycle, it represents incremental updates

b9311 is a release build version of llama.cpp, an open-source C/C++ framework for large language model inference. The project enables LLM inference in C/C++ , offering optimized performance across var

Build b9315 is a release version of llama.cpp, a C/C++ implementation for LLM inference. As an intermediate build in the llama.cpp development sequence, b9315 likely includes bug fixes, performance im