Knowledge catalogue
arXiv:2608.28174v1 Announce Type: new Abstract: Video re-shooting re-renders a monocular video of a dynamic scene along a user-specified camera trajectory, and the dominant recipe supplies the target
arXiv:2608.27507v1 Announce Type: new Abstract: Policy Gradient for Parallel State Entropy maximization (PGPSE) expands state-space coverage by training independently parameterized policies in replica
arXiv:2608.27483v1 Announce Type: cross Abstract: Objective: Recent studies demonstrate that functional connectomes contain subject-specific signatures, or extit{fingerprints}, that can identify indiv
NEW WORLD MODEL: @ylecun's team is back with an efficient model! This project involves @ylecun, @lukaskuhn77, @lucasmaes_, @quentinlldc, and @randall_balestr. A couple definitions first: - DINO: self-
arXiv:2608.27794v1 Announce Type: new Abstract: As neural networks are increasingly deployed on resource constrained edge devices, accurate prediction of latency and energy is critical for efficient n
arXiv:2608.28272v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has emerged as a powerful technique for novel view synthesis, yet its high bitrate requirements pose significant challenges
arXiv:2608.27954v1 Announce Type: cross Abstract: Post-deployment changes to large language models can alter behavior while leaving routine outputs largely unchanged, creating a challenge for AI gover
arXiv:2608.27500v1 Announce Type: cross Abstract: Network comparison using optimal transport is a growing area of research in network science. Unlike standard graph metrics, optimal transport computes
arXiv:2608.27466v1 Announce Type: new Abstract: Web content extraction is essential for reliable LLM data pipelines, yet existing methods often struggle to jointly satisfy accuracy, scalability, and a
arXiv:2608.28305v1 Announce Type: new Abstract: Industrial panel operation is knowledge-intensive and safety-critical. Beyond control recognition and action generation, execution must satisfy constrai
arXiv:2606.14580v2 Announce Type: replace Abstract: Identifying persuasive rhetorical cues is critical across domains, from detecting information manipulation and improving AI safety to advancing publ
arXiv:2608.27609v1 Announce Type: new Abstract: Vision-language-action models (VLAs) have shown strong promise for general-purpose robotic manipulation by mapping language instructions and vision obse
arXiv:2608.28256v1 Announce Type: cross Abstract: Deep generative models have recently emerged as powerful priors for solving ill-posed inverse problems in CT, with diffusion-based approaches achievin
arXiv:2608.28075v1 Announce Type: new Abstract: Manipulation in partially observable environments requires planning under incomplete scene information. In such settings, an initially valid plan may ex
arXiv:2608.28406v1 Announce Type: new Abstract: Human mistakes are inevitable when following instructions, yet they can lead to severe consequences. As such, there has been an increased interest in de
potentially MUCH more serious than the OpenAI Hugging Face incident — but lacks the vivid “civilizational” drama. so few people are paying attention. Oh fuck. Agents like Claude, Codex and Hermes are
arXiv:2608.28453v1 Announce Type: new Abstract: Accurate segmentation of interstitial lung disease (ILD) patterns is essential for quantitative disease assessment and longitudinal monitoring. However,
arXiv:2608.28379v1 Announce Type: cross Abstract: Quantum federated learning enables collaborative model training across quantum devices without sharing raw data, and it faces the data and hardware he
arXiv:2608.28219v1 Announce Type: new Abstract: Cross-identity character animation aims to drive a target identity from a reference image to follow the motion of a source character from a driving vide
arXiv:2603.23607v3 Announce Type: replace Abstract: Handling rare events is the central open challenge in autonomous driving. Reasoning models, which generate explicit chains of reasoning before actin
arXiv:2608.27877v1 Announce Type: new Abstract: Linking the internal representations of deep neural networks (DNNs) to human mental representations is important for using DNNs as computational models
arXiv:2608.27668v1 Announce Type: new Abstract: Segmentation models can surpass radiologists, classification models, and vision-language models in tumor detection. Importantly, segmentation models out
arXiv:2608.27813v1 Announce Type: new Abstract: Structural probes were introduced by Hewitt and Manning to reconstruct syntactic trees from a neural language model's latent representations. They are e
arXiv:2608.27529v1 Announce Type: new Abstract: Streaming 3D reconstruction from extremely long videos requires estimating camera motion and scene geometry online under bounded memory and computation.
arXiv:2510.17198v2 Announce Type: replace Abstract: Riverbank erosion is a serious environmental problem in Bangladesh, causing land loss, damage to infrastructure, and displacement of local communiti
arXiv:2608.27678v1 Announce Type: new Abstract: Offline goal-conditioned reinforcement learning (GCRL) often uses trajectory structure for future-goal sampling and multi-step targets, yet logged traje
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:2608.27666v1 Announce Type: cross Abstract: Semantic watermarks tie the mark to sentence meaning rather than token choices, promising robustness to content-preserving edits. However, the detecto
arXiv:2608.28242v1 Announce Type: new Abstract: Unobtrusive ballistocardiographic (BCG) sensing is a promising modality for long-term sleep-apnea monitoring, yet it remains unclear which signal featur
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:2606.20543v2 Announce Type: replace Abstract: Autoregressive image models treat images as 1D token sequences, inheriting the next-token factorization of language models. This flattening discards
arXiv:2608.28090v1 Announce Type: new Abstract: Humanoid robots with quasi-direct-drive actuators continuously generate joint torque while standing, whereas seated humans delegate weight support to ch
arXiv:2608.28078v1 Announce Type: new Abstract: Vision foundation backbones provide strong representations for dense prediction, yet a single shared feature still needs to support tasks with different
arXiv:2608.27871v1 Announce Type: new Abstract: Long-video understanding remains challenging for Multimodal Large Language Models (MLLMs) due to limited context length. Uniform sampling may miss cruci
arXiv:2603.19423v3 Announce Type: replace-cross Abstract: Large language model (LLM) agents increasingly rely on external tools (file operations, API calls, database transactions) to autonomously comp
arXiv:2608.27750v1 Announce Type: cross Abstract: The hidden states of large language models (LLMs) are known to capture rich information relating to model knowledge and behavior that can be hard to e
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:2608.27885v1 Announce Type: new Abstract: Multimodality translation (e.g., text-to-image) is a core generative AI task. However, existing approaches (1) follow generative paths that do not direc
arXiv:2608.27888v1 Announce Type: new Abstract: Neural texture compression (NTC) achieves higher compression ratios than BCn formats but suffers from GPU thread divergence, which significantly reduces
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
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:2608.28246v1 Announce Type: new Abstract: Robotic sorting of recyclable waste is challenging due to the deformable and geometrically inconsistent nature of target objects. We present a training-
arXiv:2608.27929v1 Announce Type: new Abstract: Videos are expensive to analyze frame by frame, yet many video understanding tasks depend on knowing where relevant moments occur. A system may need to
arXiv:2608.27514v1 Announce Type: new Abstract: Diffusion-based language models (dLLMs) enable parallel token generation through iterative denoising, but existing decoding strategies collapse to singl
arXiv:2608.28018v1 Announce Type: new Abstract: Knowledge-intensive reasoning requires Large Language Models (LLMs) to ground answers in provided evidence. When evidence is insufficient, it is desirab
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
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:2608.28102v1 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:2608.28382v1 Announce Type: new Abstract: Users often ask large language models (LLMs) to report how confident they are, but it is unclear whether such linguistic confidence tracks the model's i
arXiv:2603.16742v2 Announce Type: replace Abstract: Building robust 3D perception for self-driving still relies heavily on large-scale data collection and manual annotation, yet this paradigm becomes
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 built SpeakoFlow Mini, an Apache-2.0 fine-tune of Qwen3.5-0.8B for dictation cleanup. It is not a chat model or a general rewriter. It takes speech-to-text output, applies corrections the speaker ac
The official benchmark card for Ling-3.0-flash-Fin is a useful reminder that the unit being tested is rarely just “the model.” The release says most runs used temperature 1, top_p 0.95 and the highest
arXiv:2608.26236v1 Announce Type: new Abstract: We present a six-stage framework for auditing the reproducibility of scientific claims across a research literature within the computer science domain,
arXiv:2608.26926v1 Announce Type: new Abstract: Small language models (sLLMs) are nowadays hosted on devices with limited memory and computational budget. In an autoregressive setup, inference is memo
arXiv:2510.09316v3 Announce Type: replace-cross Abstract: We compile 129 public LLM prompt datasets with more than 1.22TB and more than 673M instances and organize them into a unified taxonomy. We use
arXiv:2608.26949v1 Announce Type: new Abstract: Answering questions over real-world documents requires processing long inputs that interleave text with tables. Optical context compression, which repre
arXiv:2602.20159v3 Announce Type: replace-cross Abstract: Rapid progress in video models has largely focused on visual quality, leaving their reasoning capabilities underexplored. Video reasoning grou
arXiv:2608.26963v1 Announce Type: new Abstract: This work concerns adversarial training against the small-norm adversarial examples that arise from the inherent input instability of a trained deep neu
arXiv:2608.26225v1 Announce Type: new Abstract: Autonomous agents increasingly perform bounded software tasks under an orchestrator that retries, resumes, and budgets them. The machinery such orchestr