Knowledge catalogue
arXiv:2608.27470v1 Announce Type: new Abstract: Entity Disambiguation (ED) is a key task for constructing and using knowledge graphs. State-of-the-art neural approaches commonly model ED as a single t
arXiv:2608.28383v1 Announce Type: cross Abstract: Hybrid attention dominates frontier LLMs, yet Vision Transformers (ViTs) in multimodal LLMs lack a satisfactory hybrid design, with no consensus on wh
arXiv:2509.05193v3 Announce Type: replace Abstract: Low-rank structure is a common implicit assumption in many modern reinforcement learning (RL) algorithms. For instance, reward-free and goal-conditi
arXiv:2608.27462v1 Announce Type: new Abstract: Unlike explicit attacks with obvious profanity, implicit hate speech hides malice within seemingly compliant expressions through metaphors and contextua
https://huggingface.co/Nanbeige/Nanbeige4.2-3B-DSpark 4b model for the gpu poor that I think is stronger than qwen 3.5 9b now faster! I was getting roughly 35 t/s AR which was this models downside, it
arXiv:2511.14684v2 Announce Type: replace Abstract: Large language models (LLMs) often make reasoning errors when solving mathematical problems, and how to automatically detect and correct these error
Sori-1B is a 1B-parameter audio-language model built by a single SNU researcher whose core claim to fame is that its decoder is trained entirely from scratch on audio-paired text — no text-only pretra
arXiv:2608.28099v1 Announce Type: cross Abstract: Real-time classification during language model inference is valuable for safety filtering, behavioral analysis, and model monitoring, but current appr
arXiv:2607.15058v2 Announce Type: replace Abstract: CAD-to-image alignment aims to estimate an object's 9D pose (rotation, translation, and anisotropic scale) from a single RGB image, with application
arXiv:2608.27783v1 Announce Type: cross Abstract: Speech LLMs are usually graded after they answer, although an operating system first has to decide whether a waveform should be sent to the model. We
arXiv:2509.24192v2 Announce Type: replace Abstract: Vision-language models (VLMs) have advanced multimodal perception, demonstrated by open-vocabulary object detection with simple language queries. St
A hallucinated event, Crono awakens in his modest bedroom of 2095... I am using local models since 2025 January. My daily driver is qwen 3.6 35B A3B, which works pretty well for coding tasks, but I al
arXiv:2608.27465v1 Announce Type: new Abstract: As large language models (LLMs) are increasingly used for everyday decision-making advice, whether a model shifts the direction of its advice according
The First Golden Age of AI writing is now over. For a brief period of time, many people were better off having Claude do a lot of their writing, because it is a pretty good writer & AI detectors were
arXiv:2512.12066v3 Announce Type: replace-cross Abstract: Current safety evaluations of large language models rely on single-shot testing, implicitly assuming that model responses are deterministic an
Kirsten Korosec / TechCrunch: The Pentagon launches ChatGPT Mil and Grok for Government on its GenAI.mil platform, giving its 3M personnel access to AI tools “tailored to warfighter needs” — The Penta
arXiv:2509.04438v3 Announce Type: replace-cross Abstract: Unified models (UMs) combine visual understanding (I2T) and generation (T2I) in a single framework. We focus on T2I and I2T, where cross-consi
arXiv:2608.28393v1 Announce Type: cross Abstract: Repurchase recommenders in e-commerce are commonly framed as a binary question asking 'will this customer buy this item within W days', a formulation
Today, Transluce is releasing the most expansive independent evaluation to date of how AI systems respond to users experiencing mental health crises. We evaluated 77 model variants from OpenAI, Anthro
arXiv:2608.28138v1 Announce Type: new Abstract: Adapting video vision-language models (VLMs) is computationally expensive because video inputs produce a large number of visual tokens, making both fine
arXiv:2606.12451v2 Announce Type: replace-cross Abstract: Large language models deployed as agents over large tool catalogs face a critical tool-retrieval bottleneck. As embedding-based retrieval appr
arXiv:2608.28152v1 Announce Type: cross Abstract: Agitation fluctuates over short time horizons in people living with dementia, yet continuous physiological information for anticipating next-day risk
With b10726, the default --lazy-mode change keeps the 51B-parameter PLE n-gram embedding table of Qwen 3.8 Flash Next on disk: it is mmap'd and its rows are read on demand during inference, even with
I used Claude Code to help write this pipeline - Gemma4 to turn an idea into a short story, then IndexTTS 2.5 running on an NVIDIA 3080 to use voices from LibreVox and VTCK voices to pin as character
We’re excited to launch the official LlamaParse connector on Claude! Yes Claude can already read PDFs, and it probably works fine for relatively simple queries over relatively simple docs. But if you
arXiv:2608.27753v1 Announce Type: new Abstract: Despite the rapid advancement of Vision-Language Models (VLMs), their linguistic reach remains largely confined to high-resource languages, leaving the
arXiv:2608.27879v1 Announce Type: new Abstract: Articulated human pose provides detailed body-configuration information beyond coarse spatial relationships, but whether this detail yields greater disc
arXiv:2608.28102v1 Announce Type: cross Abstract: Digital design requires predicting how a metal surface will look later in its oxidation; this paper presents such a pipeline for copper. Given a fixed
arXiv:2608.27518v1 Announce Type: new Abstract: Continual learning (CL) and model merging (MM) both aim to obtain a single model that performs well across multiple tasks, challenged respectively by ca
arXiv:2608.27768v1 Announce Type: cross Abstract: A language model with access to tools can commit to a final claim unsupported by the evidence it has seen, even when a single available tool call woul
arXiv:2608.27481v1 Announce Type: new Abstract: Knowledge-intensive multi-hop question answering requires systems to select evidence and compose dependent facts, yet multilingual benchmarks usually tr
Hi All, I am currently contemplating an upgrade from my 5060ti 16gb. I am getting ~40t/s with 130k context on Qwen 3.8 IQ3_S HF quant. I am running llama.cpp on linux. Objective is to increase context
GLM‑5.3 demonstrates a notably lower hallucination rate compared with other contemporary large language models. According to a report by Together AI at TogetherCompute (published August 30 2026), Clau
Mayank Parmar / BleepingComputer: Anthropic signs out some Claude users, removes saved payment methods, and issues refunds after infostealer malware on user PCs hijacked sessions to drain usage — Anth
metal : add fa-vec tunings for M2 (#27940) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/43902029 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silic
ggml: allow passing alloc dependencies in graph_optimize (#27301) ggml: allow passing alloc dependencies in graph_optimize add alloc dep tests add TODO about using flat array Website: https://llama.ap
memory : copy Hadamard matrix to k_rot tensor only if it has buffer assigned to prevent crashes during context shift of unquantized K cache (#27967) Co-authored-by: Stanisław Szymczyk sszymczy@gmail.c
metal : fix null-pipeline crash for F16 src1 mul_mat/mul_mat_id (#25648) metal : fail closed on mul_mat shapes with missing F16 kernels metal : abort on nil pipeline in encoder_set_pipeline metal : ad
sycl: split long rows in TOP_K instead of one work-group per row (#27847) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/43958406 macOS/iOS: macOS Apple Si
hexagon: support for device discovery and create sessions on demand (#27785) hex-devices: add support for lazy session allocation and cleanup dev interfaces Co-authored-by: Marco Colombo mcolombo@qti.
rpc : fix pre-rdma macOS versions (#27815) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/43962220 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silic
vendor : update cpp-httplib to 0.54.0 (#27919) vendor : update cpp-httplib to 0.54.0 vendor : update cpp-httplib to 0.54.0 and 0.54.1 Website: https://llama.app Attestations: https://github.com/ggml-o
metal : Add fa-vec tuning for M3 Pro (#27963) Related issue: #27668 Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/43966636 macOS/iOS: macOS Apple Silicon
metal: add fa-vec tunings for M3 Ultra (#27999) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/43968762 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple
rpc: fix apple rdma error spew on teardown (#27908) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/43970664 macOS/iOS: macOS Apple Silicon (arm64) macOS Ap
ggml : add ggml_backend_op_alloc_size_may_expand, use it in RPC (#27960) some backends (Metal, SYCL, WebGPU) require additional memory for fleeting data for certain ops, which is reflected in their ge
common: rename --tensor-read-lazy to --lazy-mode, add -lzm shorthand (#27969) Rename the --tensor-read-lazy CLI argument to --lazy-mode, to match the internal lazy_mode parameter, and add a -lzm short
dflash: pass missing NVFP4 scales to attention operations (#28000) DFlash2 NVFP4 draft models produced almost no accepted speculative tokens because the Q, K, V, and output projection scales were not
hip : optimize Q2_0 dot-product path for gfx1201 (#26753) hip/gfx1201: optimize q2_0 vec_dot_q2_0_q8_1 with native amdgcn perm Broadened HIP's Q2_0 perm optimization Remove redundant HIP perm availabi
hip: tune rdna 3 mmq config (#26284) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/44012223 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (ar
CUDA: use the fast mm_ids_helper path for any n_expert_used (#27978) The optimized path grouped warp lanes by token and required warp_size % n_expert_used == 0, with a single hardcoded exception paddi
llama: improve TENSOR_READ_LAZY handling (#27837) force lazy tensor on cpu if lazy is on llama: improve TENSOR_READ_LAZY handling Website: https://llama.app Attestations: https://github.com/ggml-org/l
When using two GPU with llama.cpp with --split-mode layer you usually provide a --tensor-split value to fit the proportion of the allocation on each GPU, say you have 16GB + 12GB something like --tens
Leo @Synthwavedd 🚨 SCOOP: Astra recently graduated from the dogfood stage, and is now being made available to select OpenAI partners under the name 'ultima-alpha' If feedback over this weekend is posi
I'm running Muse Glimmer 30B EXL3-SC 3.00bpw H4, fully resident on my 12GB VRAM GPU at 100K context with Q8_O KV cache. It's a joy to use a dense 30B model at this size and still get 30 tok/s on a VRA
(not written by Claude, all errors and crappy text are result of too little coffee on a Sunday morning ;) Our home server is a 2018 Thinkstation P520, bought for about 600eur in 2023. It's been upgrad
Hey guys I have been working on a open source LLM development repo. Anyone can train any amount of parameter against any arch (GQA, MLA, Dense...) When I tried to implement MLA I read the technical re
Since I spent the time to figure it out and it is not like it will make me any money ever. I think I'd share with you all what I managed to cobble together. First and foremost here the relevant bits a
The intelligence in my context is an aggregate index, I called the Agentic Coding Index, across most relevant agentic coding benchmarks: SWE-bench Pro, DeepSWE v1.1, Terminal-Bench (v4, v3, v2.1), Cod
I DON’T THINK PEOPLE REALIZE HOW MASSIVE THIS IS YET @HuggingFace and @PollenRobotics just released Microduck. It is a new legged robot for 399. It passed 1 million in sales in under SEVEN hours 🤯 The