Knowledge catalogue
arXiv:2603.01059v3 Announce Type: replace Abstract: Recent advances in large language models (LLMs) have enabled increasingly capable chatbots. However, most existing systems focus on single-user sett
arXiv:2604.06211v1 Announce Type: cross Abstract: Natural language explanations produced by large language models (LLMs) are often persuasive, but not necessarily scrutable: users cannot easily verify
arXiv:2604.06438v1 Announce Type: cross Abstract: Forecasters often choose retraining schedules by convention rather than by an explicit decision rule. This paper gives that decision a posterior-space
arXiv:2505.17209v2 Announce Type: replace Abstract: Recent advances in autonomous driving research towards motion planners that are robust, safe, and adaptive. However, existing rule-based and data-dr
arXiv:2604.06950v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) are increasingly being deployed as automated content moderators. Within this landscape, we uncover a critic
arXiv:2604.07276v1 Announce Type: cross Abstract: GROMACS is a de-facto standard for classical Molecular Dynamics (MD). The rise of AI-driven interatomic potentials that pursue near-quantum accuracy a
arXiv:2604.07747v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) can improve low-k reasoning accuracy while narrowing solution coverage on challenging math que
arXiv:2604.08031v1 Announce Type: cross Abstract: Most Human-Machine Interaction (HMI) research overlooks the maneuvering needs of passengers in autonomous driving (AD). Natural language offers an int
arXiv:2604.07423v1 Announce Type: new Abstract: Physical Reservoir Computing (PRC) leverages the intrinsic nonlinear dynamics of physical substrates, mechanical, optical, spintronic, and beyond, as fi
arXiv:2512.24517v2 Announce Type: replace Abstract: Automatic speech transcripts are often delivered as unstructured word streams that impede readability and repurposing. We recast paragraph segmentat
arXiv:2604.08000v1 Announce Type: cross Abstract: Proactivity is a core expectation for AGI. Prior work remains largely confined to laboratory settings, leaving a clear gap in real-world proactive age
arXiv:2604.07230v2 Announce Type: replace Abstract: Achieving physically accurate object manipulation in image editing is essential for its potential applications in interactive world models. However,
arXiv:2603.06257v2 Announce Type: replace-cross Abstract: In this paper, we propose a novel bounded asymmetric elastic net (L_{baen}) loss function and combine it with the support vector machine (SV
arXiv:2604.06176v1 Announce Type: cross Abstract: We present an empirical study of embedding-based retrieval under realistic conversational settings, where queries are short, dialogue-like, and weakly
arXiv:2604.07990v1 Announce Type: new Abstract: The convergence of 3D geometric perception and video synthesis has created an unprecedented demand for large-scale video data that is rich in both seman
arXiv:2604.06254v1 Announce Type: cross Abstract: With the rapid growth of interconnected devices in Industrial and Medical Internet of Things (IIoT and MIoT) ecosystems, ensuring timely and accurate
arXiv:2604.06900v1 Announce Type: cross Abstract: The field of cybersecurity is confronted with two interrelated challenges: a worldwide deficit of qualified practitioners and ongoing human-factor wea
arXiv:2604.07923v1 Announce Type: new Abstract: Dynamic urban environments are often captured by cameras placed at spatially separated locations with little or no view overlap. However, most existing
arXiv:2604.07102v1 Announce Type: cross Abstract: Activation-based steering can personalize large language models at inference time, but its effects in educational settings remain unclear. We study pe
arXiv:2601.21463v2 Announce Type: replace-cross Abstract: Existing speech editing detection (SED) datasets are predominantly constructed using manual splicing or limited editing operations, resulting
arXiv:2604.08522v1 Announce Type: new Abstract: Video temporal grounding (VTG) is typically tackled with dataset-specific models that transfer poorly across domains and query styles. Recent efforts to
arXiv:2604.08401v1 Announce Type: cross Abstract: In large language model (LLM) agents, reasoning trajectories are treated as reliable internal beliefs for guiding actions and updating memory. However
arXiv:2604.06367v1 Announce Type: cross Abstract: Web agents automate browser tasks, ranging from simple form completion to complex workflows like ordering groceries. While current benchmarks evaluate
arXiv:2604.06995v1 Announce Type: new Abstract: Existing Graphical User Interface (GUI) reasoning tasks remain challenging, particularly in UI understanding. Current methods typically rely on direct s
arXiv:2604.06422v1 Announce Type: cross Abstract: Understanding when Vision-Language Models (VLMs) will behave unexpectedly, whether models can reliably predict their own behavior, and if models adher
arXiv:2604.07834v1 Announce Type: new Abstract: This paper presents an LLM-driven approach for constructing diverse social media datasets to measure and compare loneliness in the caregiver and non-car
Yet another illustration of why LLMs aren’t even close to being AGI. The world’s best LLMs are still terrible at poker. We put each model into a 200bb heads-up NLHE match against GTO Wizard AI. The be
A study commissioned by *The New York Times* and conducted by AI startup Oumi tested 4,326 Google searches using the SimpleQA benchmark, finding that Google's AI Overviews were accurate 85% of the...
Amazon released the Nova 2 model family on December 2, 2025 at AWS re:Invent, comprising Nova 2 Lite, Nova 2 Pro (Preview), Nova 2 Omni, and Nova 2 Sonic, all featuring a 1-million-token context wi...
Meta announced Muse Spark today, their first model release since Llama 4 almost exactly a year ago. It's hosted, not open weights, and the API is currently 'a private API preview to select users', but
NEW paper from Google on multi-agent research agents. It's one of the first systems that handles end-to-end LaTeX generation, targeted literature reviews, and conceptual diagrams as a decoupled, stand
Strong release! GLM-5.1 is a DeepSeek-V3.2-like architecture (including MLA and DeepSeek Sparse Attention) but with more layers. And the benchmarks look better throughout! Looks like THE flagship open
Z.ai's GLM-5.1 is a 754-billion parameter open-weight Mixture-of-Experts model released on April 7, 2026 under an MIT license, designed as a post-training upgrade to GLM-5 with a focus on long-hori...
Simon Willison tested Z.ai's GLM-5.1 using his standard 'pelican on a bicycle' SVG benchmark, and the model stood out by spontaneously generating a full HTML page with both the SVG and a separate ...
INCREDIBLE GLM-5.1 weights are now opensource > i’ve had early access to the weights for the past few days > and yeah… this one matters a lot benchmarks? > SWE-Bench Pro: 58.4 > beats Opus 4.6 (57.3)
I ran five coding tasks against nine models on one RX 9060 XT (16 GB). Each run gets a single spec file in an empty directory and has to produce solution.py and test_solution.py, run its own tests, an
https://preview.redd.it/thtq5y7zr1wh1.png?width=3706&format=png&auto=webp&s=e75b7f205d4c7d9bed8b45bf964e9535f3492a72 I only found one sloppy-ass slop channel that published see pic attached. Obviously
The new models like Qwen3.8 27B and DeepSeek V4 Flash etc., all have this terrible, Claude-sounding writing style that I can't stand. Here's an example of what I'm talking about: 'A probe that asks wh
I understand this kind of product may not be exactly right for this subreddit, but I still think it deserves some attention, as it's an LLM frontend for local engines in the first place, and can be us
we’re getting used to it by now but DeepSeek calling this a “minor update” while moving Terminal-Bench 4.0 from 31.2 to 42.3 is very funny. also reports 77.0 on DeepSWE (vs 74.0 for Opus 5 and 73.0 fo
Already posted here https://www.reddit.com/r/LocalLLaMA/comments/1x85hfj/strata_qwen_38_flash_next_fast_but_whats_it/phavui9/ , but I believe this topic deserves it's own post. The PLE, aka the n-gram
arXiv:2610.21085v1 Announce Type: cross Abstract: An ensemble of language models is a jury, not an electorate. The answers are testimony from witnesses of unknown reliability, and the question is not
A lot of real-world documents embed extremely dense charts that require humans to not only 'perceive' the chart values, but also reason over them and reconcile with other complex elements (e.g. tables
arXiv:2412.17907v2 Announce Type: replace-cross Abstract: Psychological evaluation relies on clinicians' observation and interpretation of a patient's emotional expression, which is susceptible to sub
arXiv:2610.20675v1 Announce Type: new Abstract: Agents pair reasoning models with harnesses that organize model calls, execute tools, load skill instructions, and retain history in memory. Understandi
arXiv:2610.21882v1 Announce Type: cross Abstract: Embodied spatial intelligence requires more than visual recognition: models must localize entities, reason about their relations, and express this kno
arXiv:2610.21055v1 Announce Type: new Abstract: Recursive self-improvement, in which AI systems build stronger AI systems, is one promising route to superintelligence. We study a weaker form that can
arXiv:2610.21218v1 Announce Type: new Abstract: Agentic large language models have been documented to lose reasoning capability when placed inside a harness, the software that mediates their observati
arXiv:2610.21805v1 Announce Type: new Abstract: Multimodal objects can require different partitions under different instructions, as when products in an e-commerce catalog are grouped by color, materi
arXiv:2610.21195v1 Announce Type: new Abstract: On-policy distillation (OPD) improves a student language model by training on its own generated trajectories with supervision from a stronger teacher. H
arXiv:2610.21190v1 Announce Type: new Abstract: Point cloud upsampling is essential for 3D applications but remains challenging due to sparse, under-constrained observations. Multi-view images can res
arXiv:2610.21525v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown impressive capabilities across many tasks, including processing large amounts of text, following instructions, a
Today, Reflection released Beam, its first open-weight model built to give developers, researchers, and enterprises open control and customization for frontier software engineering and long-horizon ag
A couple of weeks ago I read this Wccftech article about Patrick Moorhead's 4 Spark setup. I meant to post this a few days ago but ran some more tests first, and then my workstation had a problem afte
arXiv:2610.20786v1 Announce Type: new Abstract: Multi-modal agents have made significant progress in interacting with open worlds. However, their ability to self-evolve remains limited. Supervised fin
arXiv:2610.21720v1 Announce Type: cross Abstract: Federated LLM unlearning addresses targeted knowledge removal when forget and retain data remain distributed across private clients and are inaccessib
arXiv:2610.22259v1 Announce Type: new Abstract: State-of-the art approaches to retinal vessel segmentation typically require extensive annotations, a highly time-consuming process, reliant on clinical
arXiv:2610.22360v1 Announce Type: new Abstract: Recent advances in multimodal large language models (MLLMs) and 3D generation have expanded 3D understanding and synthesis. However, beyond visual fidel
arXiv:2610.22195v1 Announce Type: new Abstract: Orchestrating multiple agents on a complex task requires reconciling local subtask execution with global task planning. Dynamic dispatch approaches prov
arXiv:2610.22289v1 Announce Type: new Abstract: Stronger language models may increasingly construct useful procedures for themselves, reducing the advantage of developer-supplied scaffolding. We inves