Knowledge catalogue
arXiv:2608.25235v1 Announce Type: cross Abstract: Selection of trustworthy collaborators in distributed systems is critical for efficient task completion, necessitating the inference of trustworthines
arXiv:2608.25564v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) often rely on over-parameterized models to optimize coupled solution and differential-residual objectives, leav
arXiv:2509.08897v2 Announce Type: replace-cross Abstract: With the rapid advancement of multimodal retrieval and its application in LLMs and multimodal LLMs, increasingly complex retrieval tasks have
Serving automatic speech recognition (ASR) models at scale is costly when each request uses only a fraction of a GPU. Learn how NVIDIA CUDA Multi-Process Service (MPS) with NVIDIA Triton Inference Ser
arXiv:2608.24893v1 Announce Type: cross Abstract: In competitive first-person shooter (FPS) games such as Counter-Strike 2 (CS2), account-integrity review often asks whether an account's recent behavi
arXiv:2608.25168v1 Announce Type: new Abstract: In multi-view anomaly detection, more cross-view information can actually hurt. When multiple inspection views are naively fused in a reconstruction-bas
arXiv:2602.17068v2 Announce Type: replace Abstract: Human-centric traffic signal control in corridor networks must increasingly account for multimodal travelers, particularly high-occupancy public tra
arXiv:2608.24909v1 Announce Type: cross Abstract: Existing co-speech gesture generation methods are predominantly studied in offline settings, where gestures are synthesized from complete speech segme
arXiv:2608.24966v1 Announce Type: new Abstract: Vision-language models such as LLaVA-1.5-7B often hallucinate objects absent from the image when generating captions. We ask whether an interpretability
arXiv:2608.25523v1 Announce Type: new Abstract: Prefix caching introduces a fundamental tradeoff in multi-agent large language model (LLM) serving: retaining a long system-prompt key-value (KV) cache
arXiv:2608.25944v1 Announce Type: new Abstract: The rapid advancement of Large Language Models (LLMs) makes it increasingly difficult to distinguish human writing from machine-generated text. Training
arXiv:2608.25841v1 Announce Type: new Abstract: Drug synergy prediction estimates whether two drugs produce a stronger joint effect than expected from their individual activities. For drug combination
We've introduced native, agentic spreadsheet extraction 📊 into LlamaParse. Spreadsheets are a wildly different format from PDFs (or any other document format). They can span arbitrarily many rows/colu
arXiv:2608.23817v1 Announce Type: new Abstract: SHAP and LIME are now standard tools for interpreting black-box predictions, yet their outputs can vary substantially when the input is perturbed by sma
arXiv:2608.24419v1 Announce Type: new Abstract: LLM-as-a-judge evaluation is usually assessed by agreement and robustness to surface perturbations, but reliability does not establish construct validit
arXiv:2511.09790v2 Announce Type: replace-cross Abstract: Dynamical system (DS)-based learning from demonstration (LfD) is a powerful tool for generating motion plans in the operation ('task') space o
arXiv:2601.19435v2 Announce Type: replace-cross Abstract: Sustainable monetization of large language models (LLMs) remains a critical open challenge. Traditional search advertising, which relies on st
arXiv:2608.23875v1 Announce Type: new Abstract: Artificial Intelligence (AI) algorithms frequently learn creative and unexpected solutions, surprising even expert researchers who develop and study the
arXiv:2608.24046v1 Announce Type: new Abstract: When an AI algorithm makes decisions that affect more than one person, aligning it becomes a problem of social choice: how should people's divergent pre
arXiv:2608.23816v1 Announce Type: new Abstract: Quantized fine-tuning (QLoRA) saves memory but not time. It dequantizes every 4-bit weight on the fly, so it trains more slowly than fp16 LoRA. We prese
arXiv:2510.21536v5 Announce Type: replace-cross Abstract: Free-space segmentation is essential for autonomous robots to identify drivable regions and navigate safely across indoor, outdoor, and road-s
arXiv:2608.23691v1 Announce Type: new Abstract: We study autonomous mathematical discovery in the Station, an open-world multi-agent environment in which AI agents from different model families pursue
arXiv:2608.24319v1 Announce Type: new Abstract: An intelligent system does not merely reason: it governs its own reasoning - how much to compute, when to stop, which module to activate. Can that role
arXiv:2608.24217v1 Announce Type: new Abstract: We propose CARO, a contact-agnostic residual observation framework for policy adaptation. CARO embeds a fixed-base Euler--Lagrange model into the reinfo
arXiv:2608.24824v1 Announce Type: new Abstract: Large language models are increasingly used for knowledge graph question answering (KGQA), but can fail to correctly ground answers in the underlying gr
I discovered something today that I suspect a lot of AI users may not realise. I’ve been pressing 👍 on ChatGPT responses because I thought it meant: 'Yes, this is a good response, this is the register
arXiv:2608.24771v1 Announce Type: cross Abstract: Brain stroke, known for its high mortality and incidence rates, poses significant health risks and requires rapid intervention for survival. Early dia
arXiv:2603.01113v2 Announce Type: replace Abstract: Interactive task planning with large language models (LLMs) lets robots generate high-level action plans from natural language, but over long horizo
arXiv:2608.24368v1 Announce Type: new Abstract: Reliable multi-turn tool use requires an agent to preserve an evolving task state and ensure that each action remains consistent with it. However, direc
arXiv:2608.23811v1 Announce Type: new Abstract: Automated fact-checking is essential for ensuring the reliability of public health information, yet the biomedical domain poses unique challenges. Valid
arXiv:2608.23870v1 Announce Type: new Abstract: When it comes to safety policies for generative AI, one size does not fit all. Each organization and use case needs to mitigate different risks dependin
Interested in designing and building agent harnesses for long-horizon, multimodal tasks? Nomic is hiring a Harness Engineer. We're post-training models and an agent harness that can perform most tasks
arXiv:2407.00500v2 Announce Type: replace-cross Abstract: Recent point-based intrinsic decomposition and inverse rendering methods have advanced the modelling of the shading and albedo of 3D scenes. H
arXiv:2608.24845v1 Announce Type: cross Abstract: We present LAION-BVD, a large-scale open video dataset for multimodal learning, which contains 1.3B platform-specific video URLs collected from Common
arXiv:2511.20809v2 Announce Type: replace Abstract: We present Split-then-Merge (StM), a novel framework designed to enhance control in generative video composition and address its data scarcity probl
arXiv:2608.23831v1 Announce Type: cross Abstract: While reinforcement learning (RL) allows generalist robot policies to continually improve during deployment, the large model size of modern generalist
arXiv:2608.23814v1 Announce Type: cross Abstract: Large Language Models (LLMs) demonstrate strong capabilities in automated essay scoring (AES), but contemporary approaches typically employ fixed prom
Presented by Tata Communications Enterprises are deploying AI agents, voice AI, and automation across messaging, voice, and digital channels faster than the architecture meant to support it. Most of t
arXiv:2606.13856v2 Announce Type: replace Abstract: Fine-tuning a vision-language-action model (VLA-JEPA) on a single GPU should be simple: load a pretrained checkpoint, run training, deploy. There is
arXiv:2608.24082v1 Announce Type: cross Abstract: Large Language Models (LLMs) have shown strong capabilities in table reasoning, but their effectiveness degrades as tables grow in size and complexity
arXiv:2608.24427v1 Announce Type: new Abstract: Non-parametric (partial) identification of counterfactual queries typically relies on a fully specified causal graph. Motivated by settings with incompl
arXiv:2602.11684v2 Announce Type: replace-cross Abstract: As Large Language Models increasingly power role-playing applications, simulating patients has become a valuable tool for training counselors
arXiv:2407.11473v2 Announce Type: replace Abstract: Maximum entropy inference and learning of graphical models are pivotal tasks in learning theory and optimization. This work extends algorithms for t
arXiv:2506.12202v2 Announce Type: replace-cross Abstract: Large language models (LLMs) often call external tools to solve tasks. One effective strategy is for LLMs to write code, enabling them to use
Yet another vLLM fork thread here, but this time its for older INT8-centric hardware. This is a complete INT8 serving stack for Qwen3.8 27B based on vLLM, AITER, and a 27B GPTQ INT8 quant w/ DFlash2.
I am aware that I may not be able to run some higher end models, but I’m starting my journey into Ollama to learn capabilities and limits of local hosting. What could I expect to run on a Lenovo Think
arXiv:2608.23928v1 Announce Type: cross Abstract: Surgical spatio-temporal grounding (STG) requires locating, at each video time specified by a procedural question, the object that the question asks a
arXiv:2608.24275v1 Announce Type: new Abstract: Safeguarding language model agents requires assessing complete execution trajectories under context-dependent safety policies. Existing policy-aware saf
arXiv:2608.24338v1 Announce Type: new Abstract: Inference-time decoding methods improve LLM reasoning by exploring multiple candidate trajectories, yet treat each trajectory as atomic: either retainin
arXiv:2608.24426v1 Announce Type: cross Abstract: Learning operators from sequentially collected data arises in adaptive experimental design, Bayesian optimization, and dynamical-system modelling, whe
arXiv:2509.03754v2 Announce Type: replace-cross Abstract: Responding to rising global food security needs, precision agriculture and deep learning-based plant disease diagnosis have become crucial. Ye
arXiv:2608.24237v1 Announce Type: new Abstract: Longitudinal radiology report generation (LRRG) requires identifying both current findings and their changes relative to a prior study. Existing methods
There’s been a lot of debate and speculation about the Hugging Face attack over the last month, and many people have been understandably skeptical of simply taking OpenAI’s word for things. I hope our
arXiv:2608.24111v1 Announce Type: new Abstract: We propose CAT, a trajectory-level continuous action representation framework for robotic manipulation. Existing visuomotor systems often entangle actio
arXiv:2411.12965v3 Announce Type: replace-cross Abstract: Nearest neighbor (NN) algorithms have been extensively used for missing data problems in recommender systems and sequential decision-making sy
What happens when there are more agents than eyeballs browsing the internet? How will the economics of the internet be reinvented? @paraga thinks Shapley values may hold the answer. Parag built Twitte
arXiv:2608.24080v1 Announce Type: cross Abstract: In psychological counseling, effective support is not always delivered through long, information-rich responses. Minimal responses, such as backchanne
arXiv:2608.24563v1 Announce Type: new Abstract: Imaging factor disentanglement in text-to-image generation aims to independently control image acquisition properties such as types of camera lenses, se
arXiv:2608.24422v1 Announce Type: new Abstract: Recovering the full 3D spine anatomy from intraoperative ultrasound is an ill-posed inverse problem, as the complete structure must be inferred from inc
arXiv:2608.22644v1 Announce Type: cross Abstract: As the use of Artificial Intelligence (AI) and Large Language Models (LLMs) is becoming common in everyday applications, their ability to interpret na