Knowledge catalogue
arXiv:2609.26748v1 Announce Type: cross Abstract: Clustering is an unsupervised learning technique that partitions unlabeled data into groups. Most existing methods require user-specified parameters,
HIP : optimize IQ2/IQ3 (__vsub4 __vcmpne4) using SWAR (#27962) HIP : use bit manipulation for __vcmpne4 HIP : use bit manipulation for __vsub4 Website: https://llama.app Attestations: https://github.c
hex-dma: introduce direct-mapped DMA cache that is better suited for HVX FA mask handling (#29282) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/49404271
sampler: reduce the size of the probe (#29285) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/49443624 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple S
vulkan: hide internal symbols to prevent duplicate-dlopen state destruction (#29139) Since #28732 our internal symbols are exported. A duplicate copy dlopened and dlclosed by ggml_backend_load_all() t
sycl : support op get_rows_back, only support fp32/fp16 (#25266) resovle confict support gedt_rows_back, update the ops.md Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cp
sycl: extend MMVQ GLU fusion, add rms_norm+scale and ssm_conv+silu fusions (#28931) sycl : extend MMVQ GLU fusion to mixed quant types; add rms_norm+scale and ssm_conv+silu fusions fixing spacing issu
sycl : support new UT case for mul_mat_hadamard fp16 (#29218) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/49484593 macOS/iOS: macOS Apple Silicon (arm64
cuda: top-k MoE should always fire (#28432) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/49495074 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Sili
ggml-meta: resolve multi buffer views (#29266) ggml-meta: resolve multi buffer views add TODO to revisit if graph allocator gets refactored Website: https://llama.app Attestations: https://github.com/
vulkan: add IQ4_XS MMQ/MMV matmul kernels (#28415) vulkan: optimize IQ4_XS matmul kernels Assisted-by: OpenAI Codex vulkan: address IQ4_XS review nits drop the dead LOAD_VEC_A != 8 branch in the IQ4_X
make-release : update summary prompt Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/49525233 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (ar
model : support Gemma4 DSpark draft backbone (#29226) dspark: add Gemma 4 draft support Add GGUF conversion and runtime support for full-attention and SWA Gemma 4 DSpark drafts, including tied output
server: Dedup the draft HF model via dedup-cache-models (#27934) server: Dedup the draft HF model via dedup-cache-models Fixes #27846 server: avoid capturing structured binding in lambda Website: http
server: accept OpenAI video_url content type and data: video URIs (#27921) The OpenAI chat completions API specifies content part type 'video_url' with a {'url': ...} object, and clients typically sen
jinja : parse unary +/- before variables (#29244) jinja : parse unary +/- before variables Lexer already emits unary_operator for -n / +n, and runtime executes unary -. Parse them at multiplicative pr
server: fix token counting API crash on sleep (#29309) server: wake up sleeping server correctly server: wake up sleeping server correctly (local aliases removed) Website: https://llama.app Attestatio
CUDA: enable sparse-fa for dsv4 prefill (again) (#29298) CUDA: enable sparse-fa for dsv4 prefill (again) CUDA: unroll the query loop of the sparse mask scan The query loop of flash_attn_mask_to_sparse
llama.cpp : bump version to 0.5.0 (#29333) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/49623059 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silic
opencl: add A8 Q6_K non-MoE dp4a binary kernel (#29057) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/49630180 macOS/iOS: macOS Apple Silicon (arm64) macO
tests: add -b/--backend option to test-llama-archs for testing a specific backend (#27372) tests: add backend option to test-llama-archs Update tests/test-llama-archs.cpp Co-authored-by: Johannes Gäßl
arXiv:2609.24921v1 Announce Type: new Abstract: Scientific weak signals are early, low-visibility research directions that later become central to mature scientific topics, yet existing resources such
arXiv:2609.25040v1 Announce Type: cross Abstract: Banana crop diseases threaten food security across the world, yet field diagnosis remains difficult because of limited expert access and visual simila
Banger paper from Microsoft Research and colleagues. It studies the potential benefits of agents that share progress while they work. (bookmark it) Communication is still a challenge with multi-agent
Banger paper from Stanford and Together AI. They show why it might be a good idea to let your agent team learn its own way of working together. (bookmark it) Three models (o3-mini, Claude Sonnet 4 and
arXiv:2609.25891v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) often struggle with fine-grained visual perception when processing complete images, as critical evidence may on
arXiv:2410.07421v2 Announce Type: replace Abstract: Instance segmentation is a core computer vision task with great practical significance. Recent advances, driven by large-scale benchmark datasets, h
arXiv:2609.26088v1 Announce Type: new Abstract: This study introduces a novel hybrid CNN-Transformer architecture to address the limited progress in Bengali SLR, focusing on isolated sign word recogni
arXiv:2609.23152v1 Announce Type: cross Abstract: Recently proposed self-supervised audio encoders learn powerful general-purpose representations of sound scenes, yet they are spatially blind. To supp
arXiv:2609.26481v1 Announce Type: cross Abstract: Social norms cannot be identified from behavior alone: the same cooperative equilibrium may reflect shared expectations, strategic incentives, or simp
arXiv:2609.25859v1 Announce Type: new Abstract: Biomedical Entity Linking disambiguates mentions to entities in a knowledge base (KB), making it the cornerstone of information extraction pipelines. Wh
arXiv:2609.26490v1 Announce Type: new Abstract: This study introduces an interdisciplinary framework for benchmarking robots deployed in public environments, addressing the gap between traditional lab
arXiv:2609.25735v1 Announce Type: new Abstract: Class-balanced replay controls class frequency but does not determine the interval between successive replay appearances of a class. We study this inter
arXiv:2609.26567v1 Announce Type: new Abstract: Robots that store past experiences must select which one to reuse in a new scene. Most systems select by visual similarity, and most evaluations report
arXiv:2609.24663v1 Announce Type: new Abstract: Self-evolving agents convert interaction feedback into persistent artifacts, such as memories or skills, which in turn guide subsequent decisions. As th
arXiv:2609.26216v1 Announce Type: new Abstract: A correct teacher solution becomes useful supervision when the receiving student can continue its reasoning. We measure this compatibility with prefix r
arXiv:2609.24515v1 Announce Type: cross Abstract: AI agents are being deployed rapidly, accompanied by a growing number of AI-specific attacks and corresponding incidents. As incident reporting become
arXiv:2609.23421v1 Announce Type: cross Abstract: Standard data center sustainability metrics, including Power Usage Effectiveness (PUE), Water Usage Effectiveness (WUE), and Carbon Usage Effectivenes
arXiv:2609.22747v1 Announce Type: cross Abstract: Understanding the performance of large-scale recommender systems remains an underexplored challenge, especially for content creators and model develop
arXiv:2609.25820v1 Announce Type: cross Abstract: Discrete action tokenization is central to autoregressive vision-language-action (VLA) models, yet action representations are often evaluated primaril
arXiv:2609.26704v1 Announce Type: new Abstract: Large language models increasingly tackle hard reasoning problems by spending more test-time compute, yet the dominant strategy remains naive repeated s
arXiv:2609.25916v1 Announce Type: new Abstract: Mixed-precision weight quantization is commonly formulated as a Multiple-Choice Knapsack Problem (MCKP), yet existing solvers rely on scalar sensitivity
arXiv:2609.25007v1 Announce Type: cross Abstract: The performance of state-of-the-art speaker verification (SV) systems severely degrades on short utterances due to insufficient speaker-specific infor
arXiv:2609.26208v1 Announce Type: new Abstract: Data visualization is central to analytical reasoning, but real-world analysis increasingly requires language-driven interactive interfaces rather than
arXiv:2609.25271v1 Announce Type: new Abstract: Sidescan sonar is a common sensor for both manned and autonomous marine exploration and mapping, yet very few methods build upon or exploit the geometri
arXiv:2508.09297v4 Announce Type: replace-cross Abstract: Artificial intelligence (AI) increasingly shapes how people think, engage, and evaluate information. To minimize risk, most current systems ar
arXiv:2503.15242v3 Announce Type: replace Abstract: We introduce BigO(Bench), a novel coding benchmark designed to evaluate the capabilities of generative language models in understanding and generati
Radical Numerics, led by CEO Eric Nguyen, is deploying “biological chain‑of‑thought” and multimodal perception techniques to stay ahead of the evolving bio‑defense arms race, enabling rapid design of
arXiv:2609.26346v1 Announce Type: new Abstract: Political discourse is widely perceived to be growing more hostile, yet robust evidence remains scarce. This study examines blame attribution in the Dan
arXiv:2609.26147v1 Announce Type: new Abstract: Modern LLMs are deployed as families of post-trained variants (base, instruct, chat, code) derived from a shared set of pre-trained weights. We present
arXiv:2609.26021v1 Announce Type: new Abstract: Dynamic black-box optimization presents significant challenges for Bayesian Optimization (BO), as the objective function evolves over time, causing opti
arXiv:2609.25486v1 Announce Type: new Abstract: Forceful manipulation is challenging for humanoid robots because interaction forces can disturb whole-body balance. We introduce the Supporting Hand Str
arXiv:2609.25146v1 Announce Type: new Abstract: Continual learning, the ability to learn from sequential experience while retaining and adapting prior knowledge, is central to intelligent systems oper
arXiv:2609.24324v1 Announce Type: new Abstract: Electroencephalography (EEG) provides a non-invasive window into dynamic brain activity, yet modeling long-horizon EEG sequences remains challenging due
arXiv:2609.25947v1 Announce Type: cross Abstract: Quantum circuit optimization replaces a circuit with an equivalent one of fewer gates and lower depth, reducing execution cost and error rate. We ask
arXiv:2508.20517v2 Announce Type: replace-cross Abstract: Cross-chain bridges enable asset and state transfers across heterogeneous blockchains, but their complex cross-domain interactions introduce n
arXiv:2609.26214v1 Announce Type: new Abstract: We present a methodology that places a 3D digital twin (DT) of the environment as the main enabler behind the development of radio sensing at scale. The
arXiv:2609.22696v1 Announce Type: new Abstract: Decentralized social media platforms create new opportunities and challenges for computational mental health research because data access, moderation, l
arXiv:2609.25693v1 Announce Type: new Abstract: Object detection in adverse weather remains challenging because severe degradations weaken visual quality and disrupt semantic feature representations a
arXiv:2609.25606v1 Announce Type: new Abstract: Cable routing requires coordinated control of global cable topology and changing local contacts. We present CableVLA, an end-to-end multimodal vision-la