arXiv:2604.09686v1 Announce Type: new Abstract: Traditional neural network models for intent inference rely heavily on observable states and struggle to generalize across diverse tasks and dynamic environments. Recent advances in Vision Language Models (VLMs) and Vision Language Action (VLA) models introduce common-sense reasoning through large-scale multimodal pretraining, enabling zero-shot performance across tasks. However, these models still lack explicit mechanisms to represent and update belief, limiting their ability to reason like humans or capture the evolving human intent over […]

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arXiv:2507.21429v2 Announce Type: replace Abstract: Gradient descent (GD) on deep neural network loss landscapes is non-convex, yet often converges far faster in practice than classical guarantees suggest. Prior work shows that within locally quasi-convex regions (LQCRs), GD converges to stationary points at sublinear rates, leaving the commonly observed near-exponential training dynamics unexplained. We show that, under a mild local Neural Tangent Kernel (NTK) stability assumption, the loss satisfies a PL-type error bound within these regions, yielding a Locally […]

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Key Highlights: This launch marks a big shift. AI tools are evolving from simple assistants that generate text or code into platforms that can produce full creative outputs. With Claude Design, Anthropic isn’t just chasing the chatbot crowd; it’s aiming to become a productivity platform for all kinds of professional work. The timing is perfect as more and more people are looking for tools that can handle complex tasks in one, prompt-driven experience. At its core, Claude Design […]

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Artificial Intelligence has its own way of impressing us with its potential and wonders. It is an incredibly growing field and will definitely have an immense effect on our lives. In my opinion, automating manual labor and work sounds like an amazing idea; people wouldn’t need to bother about whether there is going to be traffic in their route to work, or you wouldn’t have to review through spelling/grammar errors in your lengthly research paper for English. AI […]

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The expanding scale of neural networks poses a major challenge for distributed machine learning, particularly under limited communication resources. While split learning (SL) alleviates client computational burden by distributing model layers between clients and server, it incurs substantial communication overhead from frequent transmission of intermediate activations and gradients. To tackle this issue, we propose NSC-SL, a bandwidth-aware adaptive compression algorithm for communication-efficient SL. NSC-SL first dynamically determines the optimal rank of low-rank approximation based on the singular value […]

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The Ghost in the Codebase Elena, a newly promoted squad lead, stares at her screen at 9 PM on a Thursday. Her Slack icon bounces with a message from her product manager asking for a quick ETA on the new invoice feature. Elena winces. She cannot give an ETA because her team has spent the last three days just trying to seed the local database. They have just inherited a pristine billing system featuring seven microservices, a custom […]

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Large Language Models (LLMs) often produce hallucinated or unverifiable content, undermining their reliability in factual domains. This work investigates Reinforcement Learning with Verifiable Rewards (RLVR) as a training paradigm that explicitly rewards abstention ("I don’t know") alongside correctness to promote intellectual humility. We fine-tune and evaluate Granite-3.3-2B-Instruct and Qwen-3-4B-Instruct on the MedMCQA and Hendrycks Math benchmarks using a ternary reward structure ($-1$, r_abs, 1) under varying abstention reward structures. We further study the effect of combining RLVR with […]

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Hi, I have couple of papers under consideration in OSDI ’26 and VLDB ’26 – and would like to pre-publish them in Arvix. Can anyone with endorsement rights in cs.DS or cs.AI or other related fields can please endorse me? https://arxiv.org/auth/endorse?x=6WMN8A Endorsement Code: 6WMN8A submitted by /u/rch0wdhury [link] [comments]

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