Knowledge catalogue
Agentic RL is hard at every layer: environments, training infra, and algorithms. So we’re open-sourcing all of it. For environments, that means both the dataset and the scalable synthesis + quality-co
arXiv:2610.01618v1 Announce Type: new Abstract: Agent evaluations increasingly go beyond a single success rate, reporting metrics such as cost, consistency, and robustness. Yet they typically treat th
arXiv:2610.01813v1 Announce Type: new Abstract: Mitotic counting is an important component of tumour grading, diagnosis and prognostic assessment across several tumour types, but manual assessment is
arXiv:2610.02069v1 Announce Type: cross Abstract: Rare weather regime transitions pose a challenge for data-driven modeling due to class imbalance. In this study, we develop a probabilistic deep learn
Every information technology leader I talk to has an artificial intelligence story about customer experience. Almost none has an outcome story. That gap is now measurable. Talkdesk Inc., in partnershi
Learn three ways to get noticed and grow your career as AI reshapes how developers build software. The post AI is rewriting the developer career ladder. Here’s how to stand out. appeared first on The
Seattle-based artificial intelligence research firm Allen Institute for AI announced a development framework for large language models Thursday that significantly improves how mixture-of-experts large
Editor’s note: AI21 Labs is a leading global AI lab with a long track record of building foundation models, most notably the Jamba family, and today focuses on specialized LLMs and agent optimization
arXiv:2610.00465v1 Announce Type: cross Abstract: Next-generation large language models (LLMs) are expanding from the cloud to ubiquitous edge devices. However, edge devices typically either lack the
arXiv:2610.01389v1 Announce Type: new Abstract: Modern retrieval systems must both be automated and interactive, allowing users to search and refine results in real time. We present AiSearch, a flexib
arXiv:2610.00592v1 Announce Type: cross Abstract: In partially observable reinforcement learning (RL), a later observation can make stored information obsolete or change what it implies for the next d
arXiv:2610.01477v1 Announce Type: cross Abstract: Tracking seasonal change in crops and forests requires observing the same plants repeatedly. Ground robots can do this at close range, and a manipulat
arXiv:2610.00825v1 Announce Type: new Abstract: Dubbing quality control requires a reference-free judge that can determine whether a candidate text line matches a speaker's visible articulation in bot
arXiv:2610.00870v1 Announce Type: new Abstract: We present an educator-guided LLM pedagogical agent for scaffolded feedback in conceptual database design. Integrated into an entity--relationship diagr
arXiv:2610.01326v1 Announce Type: new Abstract: This paper presents the European Crisis Management Ontology (ECMO), a modular OWL-based ontology intended as a cross-sectoral reference for disaster ris
arXiv:2610.00665v1 Announce Type: new Abstract: Background: Protein language models (PLMs) are increasingly used for sequence generation and property prediction, but their size makes fine-tuning and d
arXiv:2610.00706v1 Announce Type: cross Abstract: Large audio-language models (LALMs) are sensitive to input perturbations, such as noise, waveform corruption, and adversarial injections. We propose A
AI agents don't just answer queries — they can autonomously issue refunds, manage inventory, execute multi-step handoffs, and orchestrate sub-agents, to name but a few complex agentic workflows. That
arXiv:2610.01721v1 Announce Type: new Abstract: Monitoring the Pantograph-Catenary System (PCS) provides insight into the health conditions of the pantograph and the railway infrastructure. Recent ind
Anthropic: Anthropic launches the Claude Frontier Academy with a $100M commitment to train 10K “Frontier Deployed Engineers” by 2028, starting with Accenture, Bain, others — The first-of-its-kind Acad
arXiv:2610.01944v1 Announce Type: new Abstract: Few-shot personalization enables large vision--language models (LVLMs) to learn user-specific visual concepts for applications such as personalized retr
arXiv:2610.00831v1 Announce Type: new Abstract: A typed decision is a choice among a fixed set of options, returned as a probability rather than as text. Systems that need typed decisions today use mo
I mean , DeepSeek, Kimi, GLM, MiniMax -- the list of Chinese LLM's is such a long freaking list. As American's -- why don't we feel .. a little funny .. about being so far behind? Chinese entrepreneur
arXiv:2610.01687v1 Announce Type: cross Abstract: Test-time scaling often seeks better answers by sampling multiple responses from a frozen model, yet conventional temperature sampling generates every
arXiv:2610.01716v1 Announce Type: cross Abstract: Artificial intelligence presents an unusually difficult problem for global governance. The technology develops rapidly, crosses borders easily, and is
arXiv:2507.17389v2 Announce Type: replace-cross Abstract: Recent advances in code large language models (CodeLLMs) have made them indispensable tools in modern software engineering. However, these mod
arXiv:2610.00854v1 Announce Type: new Abstract: Frontier vision-language models (VLMs) combine scene estimation, interaction grounding, and executable actions. Understanding how these abilities suppor
arXiv:2610.02098v1 Announce Type: new Abstract: Mechanistic interpretability aims to recover the internal computations responsible for model behavior. Progress in automated circuit discovery is often
arXiv:2610.02122v1 Announce Type: cross Abstract: Real-world enterprise data science and analytics workflows require reasoning across dozens of tables, performing statistical analyses, and acting on t
arXiv:2610.01314v1 Announce Type: new Abstract: Dynamic scenes may be captured by a moving camera, multiple video streams, or images taken at different times. These observations reveal complementary a
arXiv:2610.01692v1 Announce Type: new Abstract: Wrist electrodermal activity (EDA) differs in amplitude from one person to the next, so affect-recognition models normalize their input before classific
arXiv:2610.00052v1 Announce Type: cross Abstract: We evaluate six language-model configurations on requests for six distinct random integers from 1-49. Across 1,200 attempted calls using four English
arXiv:2601.11354v2 Announce Type: replace Abstract: Recent LLM-for-Space systems address mission planning, scheduling, operations support, simulator control, and autonomy, but their evaluations use di
arXiv:2610.01896v1 Announce Type: cross Abstract: Asynchronous reinforcement learning (RL) improves the efficiency of large language model post-training but introduces stale rollouts generated by earl
arXiv:2610.01741v1 Announce Type: new Abstract: Predictive Vision-Language-Action (VLA) models aim to improve robotic manipulation via future observation or world dynamics forecasting. However, existi
arXiv:2610.02014v1 Announce Type: new Abstract: The rapid maturation of artificial intelligence (AI) and machine learning (ML) has catalyzed a profound shift in how chemical engineering problems are f
arXiv:2610.00564v1 Announce Type: new Abstract: Operator learning on probability measures can be accomplished with transformers. For measures with polynomial tails, the exponential weighting in softma
arXiv:2610.00257v1 Announce Type: new Abstract: In standard transformer attention, a source token sends the same value vector to every receiver. The query determines how much to attend but not what to
arXiv:2610.00988v1 Announce Type: new Abstract: Cryptic ligand-binding pockets are not apparent in experimentally determined apo structures, making them difficult to identify from unbound receptor geo
arXiv:2610.01138v1 Announce Type: new Abstract: Concurrent actions in large language model (LLM) agent environments require arbitration even when each proposal is individually valid. We implement a ty
arXiv:2610.01495v1 Announce Type: new Abstract: Dynamic architectures leave a per-example routing trace beside each prediction, and diffuse routing is easy to read as a sign that the prediction is unr
arXiv:2610.01560v1 Announce Type: cross Abstract: Model intelligence and fast response jointly shape the quality of interaction with speech language models, yet remain difficult to achieve together. E
arXiv:2610.00347v1 Announce Type: cross Abstract: Self-modifying AI agents can replace, fork, and roll back identity-bearing software while descendants remain executable. Per-successor authorization d
arXiv:2610.01519v1 Announce Type: cross Abstract: Neuro-Symbolic (NeSy) predictors incorporate prior knowledge into the prediction process of neural networks, ensuring that outputs satisfy specified c
arXiv:2610.01215v1 Announce Type: new Abstract: GUI agents require high-quality interaction trajectories to learn how software environments respond to actions, maintain state, and support multi-step w
arXiv:2610.01204v1 Announce Type: new Abstract: Autoregressive modelling has achieved remarkable success in language and sequence tasks by learning to predict future states from previous observation.
arXiv:2610.01861v1 Announce Type: new Abstract: Natural language descriptions can provide rich semantic representations of audio-visual urban scenes, yet datasets that jointly describe both auditory a
Qwen4Exp: add MTP (#29761) Qwen4Exp: add MTP remove has_state member, check via ctx_bufs being non-empty consistent naming + less verbose comments cont : clean-up recurrent memory cont : clean-up comm
CUDA: Handle compute type for NVFP4 on cublass path (#29173) CUDA: Handle compute type for NVFP4 on cublass path Signed-off-by: ynankani ynankani@nvidia.com Use BF16 compute type for quantized models
llama : fix invalid assert in recurrent memory (#29799) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/52014664 macOS/iOS: macOS Apple Silicon (arm64) macO
webgpu: add bfloat16 support for MUL_MAT/MUL_MAT_ID/GET_ROWS- #29358 (#29358) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/52019658 macOS/iOS: macOS Appl
metal : release temporary private transfer buffers (#29777) metal : release temporary private transfer buffers Assisted-by: OpenAI Codex metal : fix order and formatting Co-authored-by: Niklas Wenzel
cuda : route sm70 to the Turing MMVQ nwarps table (#29753) cuda : route sm70 to the Turing MMVQ nwarps table Volta (sm_70) has no MMVQ parameter table of its own and falls through to GENERIC, which la
server: return HTTP 400 for invalid embedding requests (#29060) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/52037093 macOS/iOS: macOS Apple Silicon (arm
hexagon: shared strided DMA copy for CPY and CONCAT, any-dim CONCAT via DMA (#29685) hexagon: shared strided DMA copy for CPY and CONCAT, any-dim CONCAT via DMA hex-cpy: various fixes on top of the co
llama : clamp kpool re-pool bound to existing pools (#29805) tests : simplify function signature llama : clamp kpool re-pool bound to existing pools The n_tokens/kpool + n_seqs_unq bound on n_new_g ov
common,rpc : fix cache dir creation through symlinks on buggy libstdc++ (#29816) See https://gcc.gnu.org/bugzilla/show_bug.cgi?id=101510 Close #29759 Signed-off-by: Adrien Gallouët angt@huggingface.co
CUDA: fix 2 broken Volta FA cases (#29803) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/52093363 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silic
hexagon: add q2_k and q3_k quant type support (#29717) hexagon: add q2_k and q3_k quant type support hex-qk: consistent allocation of src1_row_size Co-authored-by: Max Krasnyansky maxk@qti.qualcomm.co
qwen4exp: fix tests (#29819) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/52169567 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (arm64, Kle