Search: “productivity”

Artificial intelligence-native cloud infrastructure giant CoreWeave Inc. says it’s going to help enterprise engineering teams to implement AI directly into their workflows through its new Physical AI

arXiv:2606.05957v2 Announce Type: replace Abstract: Singular learning theory and information geometry study the same spaces: the former in resolved coordinates, the latter in original coordinates unde

arXiv:2609.06674v1 Announce Type: cross Abstract: We present a new attack that reconstructs the text generated by locally hosted LLMs by observing CPU cache activity during detokenization. Unlike prio

arXiv:2609.06181v1 Announce Type: cross Abstract: Efficiently aggregating and orchestrating computing power across heterogeneous clusters for HPC workflows faces four practical challenges: preserving

Dreamina Seedance 2.0 is now available to US companies on fal, hosted entirely on US infrastructure. One of the world’s most capable video models can now be deployed by US teams through fal, with infe

arXiv:2609.06027v1 Announce Type: cross Abstract: Search-augmented LLM agents are increasingly used for consumer decisions, making them vulnerable to Generative Engine Optimization (GEO) poisoning. Ex

arXiv:2608.27824v2 Announce Type: replace Abstract: Evidential argumentation extends Dung's abstract argumentation by requiring arguments and interactions to be backed by chains of evidence rooted in

Artificial intelligence startup Runway Financial Inc. said today it has decided to pivot away from accounting software and rebrand itself as cfo.ai. That decision marks the launch of its new flagship

arXiv:2609.08310v1 Announce Type: cross Abstract: The success of generative retrieval has largely been attributed to the use of Semantic IDs, which improve over arbitrary item-level identifiers such a

arXiv:2609.07699v2 Announce Type: cross Abstract: Curating Web corpora for regional language variants like European Portuguese (PT-PT) is heavily bottlenecked by dialectal overlap (mainly with PT-BR)

arXiv:2609.08015v1 Announce Type: new Abstract: Long-running AI agents may read state, reason, wait for tools or human approval, and perform an external action much later. The state that justified the

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:2609.09022v1 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:2609.09090v1 Announce Type: cross Abstract: Large language models (LLMs) may abandon correct positions when users push back, exhibiting a failure mode known as sycophancy. Existing evaluations t

arXiv:2609.06737v1 Announce Type: new Abstract: Smart agriculture platforms are widely regarded as key carriers for implementing China's pesticide and fertilizer reduction, water-saving and carbon-red

Nice paper from Salesforce on co-evolving harnesses and models. Harness engineering is a hot topic right now. So this is a great read. (bookmark it) Salesforce evolved a harness with a weak model acro

Tibo / @thsottiaux: OpenAI says it will pause new 200/month ChatGPT Pro subscriptions amid “unprecedented” Astra demand; existing accounts, other plans, and API are unaffected — To make sure our curre

arXiv:2609.06127v1 Announce Type: cross Abstract: Retrieval-augmented generation is usually formulated as a statistical information-retrieval problem. Graph-based variants add relational structure, bu

arXiv:2609.05578v1 Announce Type: new Abstract: Scheduling activities in business processes can improve efficiency (e.g., reduce makespan), but is challenging because the exact sequence of activities

arXiv:2609.08196v1 Announce Type: new Abstract: This report analyzes Qiushi Engine v0.8 across all 40 test tasks in AstaBench E2E-Bench-Hard, a benchmark that requires autonomous agents to carry a res

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-

Part 4 of the same box. Part 1 was 17 -> 25-29 t/s with the expert cache PR, part 2 was 37-41 t/s after switching to UD-Q4_K_XL and stacking MTP on the cache, part 3 was the top-k fallback that was so

Recommended read. Interaction horizon scheduling is an underexplored control problem in agentic RL This paper from the Qwen team takes a closer look at the problem. Scaling the maximum number of envir

arXiv:2609.10363v1 Announce Type: new Abstract: SceneHI is a framework that lifts high-resolution, illumination-aware priors from 2D diffusion models to perform 3D texture synthesis. It is the first t

arXiv:2609.09159v1 Announce Type: new Abstract: The topological gap Delta -- the excess H_1 total persistence of a critical point cloud over a density-matched null -- scales as Delta sim L^{d+eta}. We

arXiv:2609.05631v1 Announce Type: cross Abstract: A voice agent has to decide, at every pause, whether the user has finished speaking. Without a model of the language that decision falls back to a fix

arXiv:2609.05643v1 Announce Type: new Abstract: This Comment emerges from TPC26 (https://tpc26.org), a conference convening leaders from academia, national laboratories, and industry who are reshaping

arXiv:2601.18930v5 Announce Type: replace Abstract: We are interested in enabling autonomous agents to learn and reason about systems with hidden states, such as locking mechanisms. We cast this probl

arXiv:2609.05920v1 Announce Type: cross Abstract: Agent Skills combine instructions with files, packages, tools, models, and services, so operational identity can exceed a signed directory. Recursive

arXiv:2609.10033v1 Announce Type: new Abstract: Learning-based motion planners pay at training what classical planners pay per query. Trained in world coordinates, they relearn the same motion at ever

arXiv:2609.05531v1 Announce Type: cross Abstract: No specification says how a governed autotelic AI agent organization, where agents pursue self-generated goals inside guardrails, should be designed a

arXiv:2609.09854v1 Announce Type: cross Abstract: Low-bit quantization can achieve high recall on some vector representations and fail sharply on others, while average distortion and global rank corre

arXiv:2601.12053v2 Announce Type: replace-cross Abstract: While foundation models have achieved remarkable results across a diversity of domains, they still rely on human-generated data, such as text,

arXiv:2503.00140v3 Announce Type: replace-cross Abstract: Machine learning systems deployed in distributed or federated environments are highly susceptible to adversarial manipulations, particularly a

arXiv:2609.08725v1 Announce Type: new Abstract: In online A/B tests for real-time bidding (RTB), control and treatment models are typically trained on a shared serving log that includes data generated

Banger report from Microsoft. (bookmark it) They show that it's possible to build competitive small coding agents without traditional distillation from frontier models. This is a big deal! The work de

arXiv:2609.06060v1 Announce Type: new Abstract: Long-term electricity-consumption profiles exhibit several simultaneous periodic structures, including daily, weekly, and annual cycles. This work intro

arXiv:2510.25323v4 Announce Type: replace Abstract: Normalizing flows are deep generative models that enable efficient likelihood estimation and sampling through invertible transformations. A key chal

arXiv:2606.19376v2 Announce Type: replace Abstract: Inference costs for large language model (LLM) applications are rapidly growing, driven by surging demand and rising infrastructure cost. Users expe

arXiv:2609.08475v1 Announce Type: cross Abstract: Large language models have collapsed the cost of producing lexically elaborate prose, and whether peer reviewers still reward it is a question about t

arXiv:2609.08381v1 Announce Type: new Abstract: Equivariant networks are commonly trained with Adam, yet recent work reports that matrix-structured optimizers such as Muon can perform better on these

arXiv:2609.05846v1 Announce Type: cross Abstract: In function-on-function regression, the coefficient surface eta(s,t) may exhibit complex support structure---from localized patches to global patterns

arXiv:2603.25565v2 Announce Type: replace Abstract: Current Large Multimodal Models (LMMs) in Earth observation are predominantly evaluated on planar optical tasks and often neglect the vertical dimen

arXiv:2311.01327v3 Announce Type: replace Abstract: We investigate the contextual bandits with knapsack (CBwK) problem in a high-dimensional linear setting, where the feature dimension can be very lar

I like this framing a lot: agent improvement is harness improvement, not model improvement The interesting interventions are often at the tool boundary: - what context you pass - when tools are provid