Knowledge catalogue
Amazon Web Services Inc.’s Strands Labs team has been playing around with an emerging class of lightweight artificial intelligence systems known as “decision models,” and it’s now making the fruits of
llama : preserve original batch order for speculative decoding layer inputs (#29019) llama: preserve original batch order for layer inputs Assisted-by: Codex tests: cover layer-input order across KV l
args: fix cli download mmproj arg (#28977) tests: add tests for cli download arg parsing args: fix cli download mmproj arg Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cp
Hexagon: optimize ALLREDUCE with support for safe scatter mode (#29757) hex-allreduce: add support for safe scatter mode hex-allreduce: pare down excessive comments hex-allreduce: re-write to remove r
cuda: guard the iq4_nl dequantize row kernel against short rows (#29683) dequantize_block_iq4_nl writes QK_K values per block, but a row can be shorter than that (an IQ4_NL row is only guaranteed to b
ggml-opencl : replace alloca() with std::vector (#29765) Signed-off-by: Adrien Gallouët angt@huggingface.co Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/
webgpu: fix SSM_SCAN binding aliasing (#29750) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/51685637 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple S
model : re-enable -sm tensor for qwen4exp (#28569) #27941 disabled -sm tensor for qwen4exp because test-llama-archs asserted on the Meta device once the fixture carried a PLE layer: GGML_ASSERT(ggml_b
metal : use bf16 math for mxfp4 mul-mat (#29770) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/51752863 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple
llama-bench : fix verbosity filter to show GGML_LOG_ERROR (#28229) bench : fix verbosity filter to show GGML_LOG_ERROR (#28107) bench: remove dead variables Website: https://llama.app Attestations: ht
vocab : honor BOS/EOS settings for PLaMo-2 and PLaMo-3 (#29734) vocab : honor BOS/EOS settings for PLaMo-2 and PLaMo-3 The original tokenizer configs for PLaMo-2 and PLaMo-3 have add_bos_token: true a
opencl: mark vec subgroup bcast as supproted for Adreno E17 compiler (#29698) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/51780568 macOS/iOS: macOS Appl
common : add LLM-jp-4.1 Harmony dialect handler (#29681) LLM-jp-4.1 uses the GPT-OSS format, but its tokenizer decodes a space after every special token and parallel tool calls are separated by <|end|
BLAS : Document AOCL-BLAS build and label the device AOCL-BLAS (#29640) BLAS : Document AOCL-BLAS build and label the device AOCL-BLAS AOCL-Blas : Add an AOCL-BLAS Quick Start and drop the fixed versi
hex-workqueue: fix race condition in seqn getting out of sync with idx_read/write (#29785) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/51906249 macOS/iO
HIP: avoid treating CDNA as dgx spark for gqa_ratio 20 in fattn_mma dqk 576 (#29572) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/51919562 macOS/iOS: mac
llama-mmap : avoid a second full-size copy of each tensor with direct-io (#29749) Assisted-by: Claude Co-authored-by: Pranesh Gonegandla pgonegandla@nvidia.com Website: https://llama.app Attestations:
jinja : skip copying loop scope unless a loop filter needs it (#29776) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/51940374 macOS/iOS: macOS Apple Silic
meta: clear inactive AllReduce shards with FILL, not SCALE (#29793) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/51949614 macOS/iOS: macOS Apple Silicon
mtmd: cap max_image to ubatch for non_causal models (#29773) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/51957111 macOS/iOS: macOS Apple Silicon (arm64)
babe, wake up. Hugging Face just dropped a new banger article about RL training coding agents on different harnesses. 1/ Excited to release The ultimate guide to multi-harness RL The same model behave
arXiv:2609.39813v1 Announce Type: new Abstract: Low-precision training rounds tensors that the backward pass reads again, often for several gradients; each use can read the forward's rounded value, th
arXiv:2609.39047v1 Announce Type: new Abstract: Interactive video generation (IVG) models have achieved remarkable progress in producing controllable visual content guided by user-defined actions, yet
arXiv:2609.39660v1 Announce Type: new Abstract: Generative models are transforming Bayesian computational imaging, yet the field still lacks physics-aware foundation models. Current practice falls int
arXiv:2609.38659v1 Announce Type: cross Abstract: We study multi-armed bandits (MAB) with multiple optimal arms, motivated by the fact that many practical decision making problems admit multiple corre
Banger paper from Meta and colleagues. (bookmark it) They discuss benefits of giving your agent write access to its own context. In other words, they investigate how effective it is to allow a languag
arXiv:2609.38820v1 Announce Type: cross Abstract: With the rapid growth of Arabic NLP, several models, datasets and benchmarks have been reported. This paper asks whether approaches developed for majo
arXiv:2609.40085v1 Announce Type: cross Abstract: Echolocating bats can navigate dark and cluttered spaces using echolocation. Over a decade ago, BatSLAM showed that a robot with a biomimetic binaural
arXiv:2609.39843v1 Announce Type: cross Abstract: Density estimation is a fundamental problem in statistics and machine learning. In this work, we introduce BayesNDE, a neural density estimator based
arXiv:2609.34211v2 Announce Type: replace Abstract: In financial fraud detection, rich semantic context can provide important evidence for transaction behavior modeling and fraud reasoning. However, p
arXiv:2609.38527v1 Announce Type: new Abstract: This work evaluates the direct transfer of a co-evolved communication protocol from a 2D simulation to a 3D physical environment, without retraining the
arXiv:2609.40269v1 Announce Type: new Abstract: Multi-Agent Path Finding (MAPF) aims to find collision-free paths for multiple agents in a shared environment. Classical MAPF assumes that all static ob
arXiv:2609.39342v1 Announce Type: cross Abstract: Intrinsic motivation plays a central role in adaptive and goal-directed behavior by conferring agents reward-independent objectives and biases useful
arXiv:2609.39139v1 Announce Type: new Abstract: Adaptive RAG uses signals such as confidence, relevance, support, and retrieval quality to decide when to search or correct evidence. In multi-step retr
arXiv:2609.38886v1 Announce Type: new Abstract: Recent advances in robot learning have enabled manipulation policies to perform increasingly diverse tasks and generalize across environments. However,
arXiv:2609.39203v1 Announce Type: new Abstract: Accurate velocity measurement is a fundamental requirement for autonomous surface and underwater vehicles. Commonly, velocity is provided by a Doppler v
Hey guys, Looking for an alternative for Claude Cowork: Project Work / Documents Integrations like Notion, Gmail, etc. Tools like Websearch, PDF creation, etc. Came over Eigent (https://github.com/eig
arXiv:2609.39958v1 Announce Type: new Abstract: Corporate and investment banking teams use presentations to support credit decisions and advise clients on financing and transactions. Producing these d
arXiv:2609.39687v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) trains mathematical reasoning models using a privileged teacher that sees a reference solution and supervises student
arXiv:2609.39816v1 Announce Type: new Abstract: Fast matrix multiplication saves multiplications through exact cancellation, but rounding sums that mix token rows can leave contributions from later to
arXiv:2609.38485v1 Announce Type: new Abstract: Unified multimodal models (UMMs) train image understanding and autoregressive image generation on shared parameters, and the two objectives are known to
arXiv:2609.39115v1 Announce Type: new Abstract: Understanding how learned representations respond to finite input changes is important for characterizing their sensitivity, invariances, and robustness
arXiv:2609.38359v1 Announce Type: new Abstract: High quality synthetic data is central to post training LLMs for adaptive AI applications that represent the diverse expert strategies and decisions in
arXiv:2609.40117v1 Announce Type: new Abstract: Time-series forecasting models achieve strong benchmark performance but exhibit severe systematic bias in industrial deployments. This train--deploy gap
arXiv:2609.38604v1 Announce Type: cross Abstract: Modern LLM agents increasingly tackle complex tasks through interactive, long-horizon exchanges with users, while existing benchmarks generally assume
arXiv:2609.39751v1 Announce Type: new Abstract: Planning with learned world models combines online trajectory optimization with learned value and policy functions for high-dimensional control. Because
arXiv:2609.39101v1 Announce Type: new Abstract: Equipping VLM agents with world modeling capabilities has shown strong potential for complex reasoning and long-horizon planning, while reducing the dep
arXiv:2607.28109v2 Announce Type: replace Abstract: Synthetic textbook data has improved language model pre-training, but prior work largely treats the benefit as a property of generated content or lo
arXiv:2609.39387v1 Announce Type: new Abstract: Neural operators increasingly benefit from pretraining on numerical simulations, yet adapting them for real-world prediction remains challenging. We int
arXiv:2609.38968v1 Announce Type: new Abstract: Multi-modal image fusion (MMIF) aims to form a single image by integrating shared information, preserving complementary cues, and coordinating cross-mod
arXiv:2609.39072v1 Announce Type: cross Abstract: Emotion recognition in conversation has been widely studied, but applying Large Language Models (LLMs) to continuous dimensional emotion evaluation in
arXiv:2606.13603v2 Announce Type: replace-cross Abstract: Chain-of-thought (CoT) reasoning is the dominant paradigm for inference-time scaling in language models, yet the causal influence of individua
arXiv:2609.39375v1 Announce Type: cross Abstract: A robot that observes people interacting with objects should be able to carry out later requests that refer back to those interactions. Such requests
arXiv:2609.39166v1 Announce Type: new Abstract: Persistent spatial memory enables embodied agents to navigate familiar environments across repeated visits. However, targets may move while unobserved,
arXiv:2609.39473v1 Announce Type: new Abstract: Autonomous agents increasingly rely on memory to generalize beyond their training environments. However, agents are bounded by what they have seen and b
arXiv:2511.15146v2 Announce Type: replace-cross Abstract: Conformal prediction (CP) constructs uncertainty sets for model outputs with finite-sample coverage guarantees. Yet ranking scores is straight
arXiv:2609.39646v1 Announce Type: new Abstract: Federated learning faces severe communication bottlenecks when clients upload high-dimensional model updates. Existing methods often compress these upda
arXiv:2509.13972v4 Announce Type: replace Abstract: Monitoring building construction sites requires comparing the as-planned design with the as-built state, which can be estimated in real time using S
arXiv:2609.38443v1 Announce Type: cross Abstract: We introduce BIND, a new action representation for visuomotor robot policies that binds 3D robot actions to their corresponding 2D image features, yie
arXiv:2609.38806v1 Announce Type: cross Abstract: Next-token prediction has driven remarkable progress in large language models, yet a growing body of evidence suggests that they can struggle on probl