Search: “inference”

so does this digital fly have the memory of the real fly that was scanned or what I’ve successfully run the full retained MaleCNS v1.0 fruit fly connectome, all 166,700 neurons, inside Minecraft, with

A group of incredibly talented and dedicated engineers made Cybercab happen. If you want to join them, we’re hiring AI engineers across the board: scaling, data, RL, reasoning, evals, world models, au

arXiv:2609.03337v1 Announce Type: new Abstract: Every engineered fill is specified by a maximum dry density and an optimum moisture content. Each determination needs a full Proctor test. Published cor

This research details an agentic framework that automatically generates custom GPU kernels and rigorously validates them. By integrating automated synthesis and thorough performance testing, the syste

arXiv:2609.03992v1 Announce Type: new Abstract: We present Alignment-Free Text-Audiobox (Text-AB), a unified framework for high-quality voice dubbing and full-duplex dialogue synthesis. Building on a

arXiv:2609.03258v1 Announce Type: new Abstract: Parking spot classification is a fundamental task in intelligent transportation systems, yet most deep learning approaches rely on large amounts of anno

arXiv:2609.03151v1 Announce Type: cross Abstract: Long-context reasoning for large language models (LLMs) is becoming increasingly important, but training over long sequences remains challenging due t

arXiv:2609.03953v1 Announce Type: new Abstract: Understanding the frequency of factual errors in chatbot-generated text and evaluating systems that detect these errors is critical for determining chat

arXiv:2609.03407v1 Announce Type: new Abstract: People increasingly turn to large language models (LLMs) for everyday advice, making ethically charged interpersonal problems a practical moral-advisory

arXiv:2609.03818v1 Announce Type: new Abstract: Collaborative perception enhances environment understanding through multi-agent information sharing, but its performance in real-world scenarios is cons

arXiv:2609.03394v1 Announce Type: new Abstract: Emotion recognition benchmarks often predict one emotion per text, missing many real-world scenarios where two people arrive at opposing emotions from a

arXiv:2609.03675v1 Announce Type: new Abstract: Streaming video understanding requires Vision Language Models (VLLMs) to process growing video streams and answer user questions under tight latency con

arXiv:2609.03973v1 Announce Type: new Abstract: An image editor may satisfy every regional plausibility constraint separately even when no single latent explanation fits the complete output. We formal

arXiv:2609.04070v1 Announce Type: new Abstract: Bridging the gap between the discrete reasoning of Vision-Language Models and the continuous, physics-constrained nature of autonomous driving remains a

arXiv:2609.03107v1 Announce Type: cross Abstract: Recent advances in generative speech models have made it increasingly difficult to distinguish authentic from synthetic audio, enabling new forms of f

arXiv:2509.17154v2 Announce Type: replace-cross Abstract: Hamiltonian dynamics describe a wide range of physical systems. As such, data-driven simulations of Hamiltonian systems are important for many

Despite everything that has happened, OpenAI has seemingly decided to stay competitive by burning down the only meaningful bit of safety assurance we actually have today - CoT monitoring. Completely d

arXiv:2609.03064v1 Announce Type: cross Abstract: Federated learning allows banks, hospitals, and other regulated organizations to train a shared model without moving raw records off their own servers

arXiv:2609.02900v1 Announce Type: cross Abstract: The problem is the beta a desk needs when a firm's price history is too short to trust: an S-1 filer, a recent listing, or a name just past a regime b

arXiv:2609.03673v1 Announce Type: new Abstract: Video generators build long videos by composing shorter parts, either by generating segments one after another or by autoregressively extending chunks.

arXiv:2609.02982v1 Announce Type: new Abstract: Learning solution operators across broad parameter ranges can require substantial coverage of both input functions and physical parameters, particularly

arXiv:2609.03629v1 Announce Type: cross Abstract: Recent advances in text-to-video (T2V) diffusion models have demonstrated remarkable generative capabilities, yet their reliance on loosely curated tr

arXiv:2609.04197v1 Announce Type: cross Abstract: Evolutionary prompt optimizers such as GEPA suffer from prompt bloat: each iteration appends rules and caveats, producing prompts up to 3imes longer y

arXiv:2609.03147v1 Announce Type: cross Abstract: Learning-based schedulers have been proposed to provide real-time user, target, and access point (AP) association in distributed cell-free integrated

arXiv:2609.03889v1 Announce Type: cross Abstract: Contact-rich loco-manipulation requires a bridge between semantic action generation and physical interaction control. Existing Vision-language-action

arXiv:2609.03868v1 Announce Type: cross Abstract: Target-centered gaze interaction requires more than suppressing frame-to-frame fluctuations: target acquisition produces task-aligned changes in gaze-

arXiv:2609.03724v1 Announce Type: cross Abstract: Bayesian Network (BN) fusion combines multiple input networks into a single structure, balancing dependency preservation with computational tractabili

arXiv:2609.03800v1 Announce Type: new Abstract: Federated learning is increasingly presented as a privacy-preserving advance: personal data remain on the device, and only model updates are shared. It

arXiv:2609.03553v1 Announce Type: new Abstract: Policy analysis requires more than predicting whether a proposal will pass: it requires identifying who will be affected, how those actors respond, and

Great paper on designing multi-agent systems. How many distinct communication topologies does an LLM multi-agent system actually need? This works claims that it's about six. Technical summary: Researc

arXiv:2609.03442v1 Announce Type: new Abstract: Differentiable causal discovery methods increasingly encode expert priors as forbidden-edge constraints enforced by an Augmented Lagrangian (ALM) penalt

arXiv:2609.04105v1 Announce Type: new Abstract: Blackwell's 4-bit floating-point (FP4) tensor cores do not automatically make attention faster because softmax conversion and on-chip dependencies domin

arXiv:2609.03334v1 Announce Type: new Abstract: A key bottleneck in 3D Gaussian Splatting training is the continual growth of Gaussian primitives, which increases optimization cost and slows convergen

arXiv:2412.14626v3 Announce Type: replace-cross Abstract: Recent advancements in large language models (LLMs) have demonstrated their potential in automating the scientific research ideation. Existing

arXiv:2609.02940v1 Announce Type: cross Abstract: Recent automatic speech recognition (ASR) systems increasingly integrate large language models (LLMs) to leverage their semantic knowledge, either ext

arXiv:2609.03796v1 Announce Type: cross Abstract: We introduce LLaDA-Image, a unified framework that pairs a 6B Diffusion Transformer (DiT) trained from scratch with a frozen vision-language understan

arXiv:2503.03313v4 Announce Type: replace-cross Abstract: Text-Attributed Graphs (TAGs), where each node is associated with text descriptions, are ubiquitous in real-world scenarios. They typically ex

arXiv:2609.04013v1 Announce Type: new Abstract: Early screening of chronic kidney disease (CKD) is critical for timely intervention, yet most machine learning (ML) and deep learning (DL) approaches re

arXiv:2609.03213v1 Announce Type: new Abstract: Large language models (LLMs) exhibit in-context learning capabilities, where they can learn new tasks from prompt contexts without weight updates. We co

arXiv:2603.18261v2 Announce Type: replace-cross Abstract: Neural Representations for Videos (NeRV) encode entire video sequences within neural network parameters, offering an alternative paradigm to c

arXiv:2609.03715v1 Announce Type: new Abstract: Vision-language-action (VLA) models with billions of parameters now dominate the LIBERO manipulation benchmark, but the model capacity actually required

arXiv:2609.03943v1 Announce Type: new Abstract: AI reviewers can now produce many specific criticisms, but more criticism is not necessarily a better review. A review may miss a consequential weakness

New from the LangSmith Signal. Over the last 2 weeks, we looked at which models teams reach for, and which ones are doing the work. ✅ Reach: gpt-4o-mini was used by 13% of orgs ✅ Work: gpt-4.1-mini sa

arXiv:2609.03160v1 Announce Type: new Abstract: Nastase et al. (2026) argue that large language models (LLMs) may illuminate language processing because both rely on distributed, context-sensitive rep

arXiv:2609.03694v1 Announce Type: new Abstract: Implicit neural representations (INRs) can model continuous 3D shapes with a shared coordinate decoder and per-instance latent codes. At test time, auto

arXiv:2609.04168v1 Announce Type: cross Abstract: As edge-based deep learning applications become more complex, optimizing performance on heterogeneous System-on-Chips (SoCs) presents unique challenge