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vulkan: int8 coopmat1 matmul implementation for AMD RDNA3 and RDNA4 (#27952) vulkan: add int8 coopmat quantized matmul shader apply scales inline use scalar sums probe and directly access coopmat valu
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vulkan: int8 coopmat1 matmul implementation for AMD RDNA3 and RDNA4 (#27952) vulkan: add int8 coopmat quantized matmul shader apply scales inline use scalar sums probe and directly access coopmat valu
llama: add llama_batch_ext (#24669) (wip) add llama_batch_ext wip updated design updated impl change signature unused var demo common_prompt_batch_decode fix pos tmp disable test-batch-alloc fix compa
test: flush status (#28352) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/49978694 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (arm64, Klei
cuda : add F16 kernel support for CONV_2D_DW (#29064) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/49985945 macOS/iOS: macOS Apple Silicon (arm64) macOS
hexagon: support I32 CPY and CONT (#29379) Assisted-by: OpenCode Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/49994729 macOS/iOS: macOS Apple Silicon (ar
hexagon: dynamic quantizer improvements (#29395) hexagon: fix accuracy issue in Q8_0 N=1 MUL_MAT hex-quant: fix register spills hex-mm: use dma for all dyn.quant paths Co-authored-by: Aparna M P aparm
llama-grammar: fix numeric truncation for token_id parsing (#29382) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/50007794 macOS/iOS: macOS Apple Silicon
hexagon: handle multi-sequence in concat_2d (#29344) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/50014220 macOS/iOS: macOS Apple Silicon (arm64) macOS A
sync : ggml (#29396) ggml : bump version to 0.25.2 (ggml/1642) ggml : fix ubsan error in ggml_graph_nbytes (ggml/1644) ggml : bump version to 0.25.3 (ggml/1645) sync : ggml Website: https://llama.app
metal : optimize sparse FA + clean-up (#29377) metal : cache sparse FA indices in shared memory Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-Vision-Exp metal : simplify shared memory size calculation A
arXiv:2609.26868v1 Announce Type: new Abstract: Learning-based models (e.g., visuomotor and Vision-Language-Action (VLA)) are increasingly explored for industrial robotic manipulation, where model pre
arXiv:2609.27760v1 Announce Type: cross Abstract: Federated learning enables distributed training of a shared model without requiring clients to share their raw data. However, its reliance on the inte
arXiv:2609.27269v1 Announce Type: new Abstract: Humanoid kicking requires coordinated whole-body motion and precise contact, while a banana kick demands contact mechanics that generate ball spin and a
Banger paper introducing Jev-as-a-Judge. The overall finding is that you want to use a cheap judge for most of your evals and send only the uncertain calls to a frontier model. This paper measures how
arXiv:2609.27450v1 Announce Type: cross Abstract: Vision-language-action (VLA) models handle long-horizon manipulation, yet success hinges on a few precision-critical phases where millimeter-scale err
Hi. I’m developing my first Python project (been at it a couple weeks). I built a very basic CLI ollama client. When a user sends a prompt I append the message to session['history'], save the sessio
arXiv:2609.27513v1 Announce Type: new Abstract: Autoregressive robot policies learn continuous control by predicting discrete action tokens from observations. Different tasks often share local motions
arXiv:2609.27536v1 Announce Type: cross Abstract: Behaviora is a preliminary conceptual architecture for representing agent and robot behavior, external and internal alike, in an addressable form. A b
benched 5.5 is IN-SANE. It almost broke our benchmark. I thought it was a bug. Claude Opus 5.5 is the new #1 on our writing benchmark, and it is not close at all. 2631 Elo. Second one, Fable, is at 23
arXiv:2609.27208v1 Announce Type: new Abstract: Spatial transcriptomics (ST) measures gene expression in tissue context, but dense capture grids can be costly and may repeatedly sample morphologically
arXiv:2609.28283v1 Announce Type: new Abstract: Several foundation models dedicated to hyperspectral images have recently been made available. These models are trained on large unlabeled datasets and
arXiv:2607.22115v2 Announce Type: replace-cross Abstract: Given a database S and a natural language question Q, text-to-SQL systems aim to generate an SQL query that correctly answers Q when executed
arXiv:2609.26919v1 Announce Type: cross Abstract: Event cameras promise low-latency perception for high-speed robotic systems, where even short delays can render detections stale by the time they info
arXiv:2609.27457v1 Announce Type: new Abstract: Vision-language models (VLMs) are often reported to outperform task-specific vision backbones for unmanned aerial vehicle (UAV) power-line defect assess
arXiv:2609.28339v1 Announce Type: new Abstract: Pretrained generative Diffusion Transformers (DiTs) capture rich pixel-level visual and language-conditioned structure through large-scale image and vid
arXiv:2608.24521v3 Announce Type: replace Abstract: Proactive medical dialogue requires an agent to decide what to ask from incomplete patient information. Existing information-seeking approaches comm
arXiv:2609.27356v1 Announce Type: new Abstract: A region can overlap a target object yet contribute more to another class. We test regions selected by Cluster-based Concept Importance (CCI) in frozen
arXiv:2609.27176v1 Announce Type: new Abstract: Evidence that evaluation material entered training does not reveal how much it affected evaluation. This distinction leaves a contaminated benchmark sco
arXiv:2609.28245v1 Announce Type: cross Abstract: Large language models (LLMs) have shown strong performance in creative text generation, yet their ability to produce culturally grounded and stylistic
arXiv:2609.27299v1 Announce Type: cross Abstract: Information systems (IS) researchers increasingly use quasi-experimental methods such as difference-in-differences (DiD) and instrumental variables (I
arXiv:2609.27773v1 Announce Type: cross Abstract: As Large Language Models (LLMs) move from conversational assistants to advanced agentic systems, guardrail failures can convert adversarial intents in
arXiv:2609.27615v1 Announce Type: new Abstract: In multimodal emotion recognition (MER), human affective states are inferred by integrating complementary cues from multiple modalities. In audio-text M
arXiv:2603.19713v2 Announce Type: replace Abstract: Even when it is difficult to assign absolute class labels to individual instances, relational information may still be available, such as whether tw
arXiv:2609.27932v1 Announce Type: new Abstract: Ganian et al. (ICLR 2026) proved that quantized neural network training is fixed-parameter tractable when parameterized jointly by architecture treewidt
arXiv:2609.27342v1 Announce Type: new Abstract: Cutting changes both the shape and topology of deformable objects, making accurate simulation challenging for robotic manipulation. A simulator must tra
arXiv:2609.27871v1 Announce Type: cross Abstract: In mainstream agent frameworks, a step ends when the agent's own output says it has finished. Durable-execution platforms bound retries and time, but
arXiv:2609.27650v1 Announce Type: new Abstract: Brain-to-language decoding translates neural activity associated with language production, internal speech and perception into linguistic or expressive
arXiv:2609.27275v1 Announce Type: new Abstract: Most autonomous-driving datasets record only the action executed by a behavior policy and the single future that followed, providing limited supervision
arXiv:2609.27317v1 Announce Type: cross Abstract: Infrared (IR) imaging is crucial for autonomous driving, remote sensing, and other perception tasks. However, adverse weather may introduce fake struc
arXiv:2609.28281v1 Announce Type: new Abstract: Interlocking brick assembly provides a representative testbed for evaluating real-world robotic manipulation capabilities, where diverse structural desi
arXiv:2609.26828v1 Announce Type: cross Abstract: NAND-backed storage offers the capacity needed to scale LLM prefix caching, but its block I/O path incurs CPU cache contention and host-DRAM staging i
arXiv:2609.28328v1 Announce Type: new Abstract: Accurate localization of the bronchoscope within the bronchial tree is essential for clinicians to be able to reach target lesions, perform biopsies and
btw i had no idea what i was doing when i started this but learned so much about models in the process and feel like i have a much better sense of what’s happening under the hood managing someone (an
Build a multi-account architecture that keeps each team's data in its own AWS account while giving AI agents a unified way to query across them. A central platform account runs the agent using Amazon
building in the agent space? this is your room at SF @Techweek_. think modern gatsby: black tie, red carpet, cocktails, live jazz & art deco glamour. 300+ founders, founding operators & investors acro
What is spatial reasoning? AI is moving beyond the digital world. The next generation of AI systems needs to understand and interact with physical environments, from robots to autonomous systems navig
arXiv:2609.26927v1 Announce Type: new Abstract: The objective of this article is to provide design principles and a software architecture for enabling interaction between humans and multiple agents in
arXiv:2603.27597v2 Announce Type: replace Abstract: Research on artificial consciousness increasingly shifts evaluation from behaviour to internal architecture. Theory-based indicators are used to upd
Mina Kimes posted that, despite facing backlash ('got cancelled'), she remains convinced that X (formerly Twitter) has returned to prominence. She characterizes the platform as the primary venue for i
arXiv:2609.27607v1 Announce Type: cross Abstract: An AI-generated radiology report can resemble a physician's report while omitting an abnormality, adding an unsupported finding, or reversing its pres
arXiv:2609.28090v1 Announce Type: cross Abstract: Backtest auditing is a calibration problem: high flaw recall is not useful when the model falsely flags matched clean strategies. We build a 96-item p
arXiv:2609.28449v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in coding tasks, but their ability to reason about code execution remains unclear. Existing reposit
arXiv:2609.27262v1 Announce Type: new Abstract: Production customer-support systems often require LLMs to support multiple skills, such as intent classification, question answering, summarization, or
arXiv:2609.27327v1 Announce Type: new Abstract: Video provides a rich record of human behavior, interaction, and situated contexts, offering important evidence for understanding people and conducting
arXiv:2609.27336v1 Announce Type: new Abstract: Automated red teaming often replays a fixed set of prompts, which measures known risks but cannot learn from failures found during testing. We present C
arXiv:2609.27681v1 Announce Type: new Abstract: Automated assessment of the Critical View of Safety (CVS) in laparoscopic cholecystectomy requires both recognition of the three CVS criteria and anatom
arXiv:2609.27825v1 Announce Type: new Abstract: Anomalous time series play a critical role in safety-critical domains, yet they are inherently scarce, heterogeneous, and costly to obtain. Existing tim
arXiv:2609.27745v1 Announce Type: new Abstract: This paper advocates category theory as a practical framework for structuring and improving rein- forcement learning in high-dimensional, partially obse
arXiv:2603.13768v2 Announce Type: replace-cross Abstract: Despite the strong performance of large audio language models (LALMs) in various tasks, exactly how and where they integrate acoustic features
arXiv:2609.27273v1 Announce Type: new Abstract: Computer-use agents (CUAs) increasingly act on behalf of users online. What happens when the environments they operate in have incentives that do not al