Knowledge catalogue
arXiv:2609.16601v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have made strong progress on visual question answering and image captioning, yet they still produce fluent clai
arXiv:2609.17269v1 Announce Type: new Abstract: Multimodal large language models generate natural-language responses from visual inputs, yet may mention objects absent from an image. In medication ass
arXiv:2601.09050v2 Announce Type: replace Abstract: Tonal low-resource languages are widely spoken but remain underserved by modern speech technologies. A central challenge is learning speech represen
arXiv:2609.16532v1 Announce Type: new Abstract: Continued pretraining (CPT) with data augmentation such as paraphrasing can store inside a large language model (LLM) the knowledge of a small source co
arXiv:2609.17107v1 Announce Type: new Abstract: Generative AI promises natural language access to the massive numerical telemetry of data centers and Industry 4.0 installations, yet text-to-query and
arXiv:2512.05126v2 Announce Type: replace-cross Abstract: Automatic video dubbing aims to generate high-fidelity speech that is temporally aligned with visual content. However, existing methods still
arXiv:2609.16797v1 Announce Type: new Abstract: Query-based segmentation methods have shown promising potential for surgical instrument segmentation and recognition, which is essential for scene under
arXiv:2609.17419v1 Announce Type: new Abstract: Long-horizon LLM agents must maintain task state across extended sequences of observations, actions, tool calls, and intermediate beliefs. We study thes
arXiv:2404.00727v3 Announce Type: replace Abstract: All state-of-the-art coreference resolution (CR) models involve finetuning a pretrained language model. Whether the superior performance of one CR m
arXiv:2609.14178v1 Announce Type: new Abstract: The rapid diffusion of hate speech and misinformation on social networks challenges democratic societies, since direct suppression efforts may deepen po
arXiv:2512.20257v2 Announce Type: replace Abstract: With the rise of easily accessible generative tools for creating and manipulating multimedia content, the threat of realistic synthetic alterations
arXiv:2609.15721v1 Announce Type: new Abstract: Automatic Related Work Generation (RWG) significantly reduces the human time and effort required to author the Related Work Section (RWS) of a research
arXiv:2609.15215v1 Announce Type: cross Abstract: Large Audio-Language Models (LALMs) have substantially advanced general audio understanding, yet they remain limited in fine-grained temporal percepti
arXiv:2609.15511v1 Announce Type: cross Abstract: This paper investigates the generation and human evaluation of Japanese haiku by contemporary Large Language Models (LLMs), focusing on authorship per
arXiv:2609.15054v1 Announce Type: new Abstract: Multi-Agent (MA) systems are effective at solving complex tasks that demand planning, tool use, and the synthesis of evidence from multiple sources. Exi
arXiv:2606.22906v2 Announce Type: replace-cross Abstract: Large language models have shown strong performance on software engineering (SE) tasks, yet understanding large industrial repositories remain
arXiv:2506.06977v4 Announce Type: replace-cross Abstract: Domain generalization has become a critical challenge in predictive healthcare, where different patient groups exhibit shifting data distribut
arXiv:2609.13556v1 Announce Type: cross Abstract: Large Language Models (LLMs) have shown remarkable proficiency on general-purpose tasks, yet their performance often degrades in highly-specialized te
arXiv:2609.14758v1 Announce Type: cross Abstract: Tool-augmented language models are evaluated on whether they reach the right answer, not on whether they report honestly when a tool fails to supply o
arXiv:2609.13667v1 Announce Type: new Abstract: Geospatial agents are increasingly expected to support recurring and evolving analytical tasks rather than execute isolated workflows. In such settings,
arXiv:2609.13475v1 Announce Type: new Abstract: Existing pipelines for clinical timeline extraction from case reports are evaluated using an expert reference and are limited by imperfect reference ann
arXiv:2609.15195v1 Announce Type: new Abstract: Embodied navigation requires agents to interpret visual observations, accumulate spatial knowledge, and execute actions to follow instructions or locate
arXiv:2603.23803v2 Announce Type: replace-cross Abstract: In this paper, we present DROP, high-Density Relocation-free sequential OPerations in automated valet parking. DROP addresses the challenges i
arXiv:2609.13730v1 Announce Type: new Abstract: Reliable progress in offline policy learning depends on careful reporting, well-tuned baselines, and evaluation across diverse conditions. Prior work ha
arXiv:2609.14636v1 Announce Type: cross Abstract: On-policy distillation (OPD) has become a standard approach for transferring capabilities from large teachers to compact students. Its cost, however,
arXiv:2609.14138v1 Announce Type: cross Abstract: As LLM agents become integrated into increasingly complex workflows, they must continually acquire new capabilities while retaining competence on prev
arXiv:2609.14057v1 Announce Type: new Abstract: Frontier LLMs are increasingly capable of conducting automated research, yet their creativity in this setting has not been systematically evaluated. In
arXiv:2609.15976v1 Announce Type: new Abstract: Mobile manipulators deployed across many rooms and visits should improve with experience: after discovering that a cabinet is locked or finding an objec
arXiv:2503.18460v2 Announce Type: replace-cross Abstract: Modelica is a widely adopted language for simulating complex physical systems, yet effective model creation and optimization require substanti
arXiv:2609.03301v1 Announce Type: cross Abstract: Wildfire seasons have become 84 days longer in the current days than in the 1970s, causing enormous threats to one's financial status and short- and l
arXiv:2609.14652v1 Announce Type: cross Abstract: Large Language Model (LLM) applications often transfer domain concepts into the model's context informally, through prompt prose, schema dumps, and ex
arXiv:2609.13500v1 Announce Type: cross Abstract: How much learned memory is needed to benefit from more data? We show that the two resources are governed by one predictive-energy spectrum in a positi
arXiv:2609.15475v1 Announce Type: new Abstract: A robot following language instructions needs its semantic memory to keep naming the same physical object while the SLAM pose graph underneath is optimi
arXiv:2609.13760v1 Announce Type: new Abstract: Publishing a research manuscript is a routine yet demanding part of scientific life: time-consuming, stressful, and often uncertain in outcome. Recent a
arXiv:2609.13504v1 Announce Type: new Abstract: Recent developments in feed-forward 3D reconstruction resulted in models which can recover dense scene representations and camera motion solely from an
arXiv:2609.13291v1 Announce Type: cross Abstract: We present ScorePrompts, an interactive system in which users upload a score, receive natural-language descriptions of its musical structure, ask ques
arXiv:2609.13966v1 Announce Type: cross Abstract: Video highlight detection aims to identify temporally important segments that capture the most informative or engaging events in a video. Reliable pre
arXiv:2609.14614v1 Announce Type: new Abstract: Deep learning architectures remain rigidly built upon traditional fully connected layers. While networks scale up, few challenge this foundational root.
arXiv:2609.13874v1 Announce Type: new Abstract: Multimodal clinical AI typically assumes that the waveform, report, metadata, and downstream predictions attached to a record belong to the same patient
arXiv:2609.14560v1 Announce Type: new Abstract: General-purpose object detectors lose accuracy on UAV footage, where targets span only a handful of pixels and onboard compute is limited. Prior work co
arXiv:2609.14320v1 Announce Type: new Abstract: Recently, linear attention layers have been increasingly adopted to replace softmax attention at scale for long-context modeling. However, existing cont
arXiv:2609.13158v1 Announce Type: new Abstract: Large Vision--Language Models (LVLMs) are increasingly expected to perform visual question answering (VQA) over planar media. However, existing planar V
arXiv:2603.15159v5 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have shown strong potential for code generation, yet they remain limited in private-library-oriented code generat
arXiv:2609.15467v1 Announce Type: cross Abstract: Adding answer options can lower multiple-choice scores without improving assessment validity. Turkish MMLU Pro examines this distinction using 12,000
arXiv:2603.19896v2 Announce Type: replace Abstract: Tool-using large language model (LLM) agents often face a fundamental tension between answer quality and execution cost. Fixed workflows are stable
arXiv:2609.15030v1 Announce Type: cross Abstract: External cache transfers can succeed while a hybrid language model resumes from an inconsistent state. We examine the full 45-layer GLM-5.3-Flash mode
arXiv:2609.15606v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable progress on short video understanding yet remain limited on long videos due to the l
arXiv:2609.13889v1 Announce Type: cross Abstract: Harness design has transformed the development of LLM-based agents by integrating memory, tool use, and runtime control. However, this design also int
arXiv:2606.12852v2 Announce Type: replace Abstract: Rapid advances have been made in developing general-purpose embodied agent in environments like Minecraft through the adoption of LLM-augmented hier
arXiv:2609.12254v1 Announce Type: new Abstract: The climate literature has grown faster than review teams can read it. That gap matters most for a concept like the environmental social tipping point,
arXiv:2609.12678v1 Announce Type: new Abstract: Short-video platforms have become a primary news source for the public, which has also enabled the widespread dissemination of fake news videos. We stud
arXiv:2609.12705v1 Announce Type: new Abstract: Handwritten text recognition resources are often small and distributed across collections that differ in language, script, document structure, and annot
arXiv:2609.12260v1 Announce Type: new Abstract: Large language models (LLMs) can generate biomedical hypotheses, but it remains unclear whether they truly reason from scientific evidence or simply pro
“Just-in-Time” OCR The latest agent harnesses (e.g. Cowork, Codex, Grok) do 2 passes of ad-hoc document processing when executing over a user-uploaded ‘data room’ of documents: 1️⃣ A fast and light pa
arXiv:2505.12135v2 Announce Type: replace-cross Abstract: When an interactive benchmark reports a single success rate for a language-model agent, it is rarely clear what that number measures. A failur
arXiv:2609.11943v1 Announce Type: cross Abstract: Recent advances in generative AI have substantially accelerated the creation of high-quality ad creatives, dramatically expanding the number of candid
arXiv:2609.12614v1 Announce Type: new Abstract: A 3D scene graph groups objects into rooms. When a robot is asked to fetch an object from the kitchen, that grouping is what tells it where to look. An
arXiv:2609.13135v1 Announce Type: cross Abstract: We present an approach to progressively extend the highlights of an image. Instead of reconstructing the full dynamic range of a complex scene directl
arXiv:2609.12814v1 Announce Type: new Abstract: Linear attention and state-space models provide linear-time sequence modeling, but their recurrent memory remains a second-order tensor (a matrix), limi
arXiv:2603.07357v3 Announce Type: replace Abstract: Latent generative models have emerged as powerful priors for solving inverse problems. These models typically represent a class of natural signals a