arXiv:2102.11361v3 Announce Type: replace-cross Abstract: FaCells is a method, and an exhibition, that turns model internals into line based artworks. Aligned face photographs (CelebA, 260k images, 40 attributes) are translated into vector sketches suitable for an XY plotter. We study how to ‘write’ these drawings for a sequence model, comparing absolute vs. relative point encodings […]
MiniLLM: Knowledge Distillation of Large Language Models
arXiv:2306.08543v5 Announce Type: replace-cross Abstract: Knowledge Distillation (KD) is a promising technique for reducing the high computational demand of large language models (LLMs). However, previous KD methods are primarily applied to white-box classification models or training small models to imitate black-box model APIs like ChatGPT. How to effectively distill the knowledge of white-box LLMs into […]
Reason2Attack: Jailbreaking Text-to-Image Models via LLM Reasoning
arXiv:2503.17987v3 Announce Type: replace-cross Abstract: Text-to-Image(T2I) models typically deploy safety filters to prevent the generation of sensitive images. Unfortunately, recent jailbreaking attack methods manually design instructions for the LLM to generate adversarial prompts, which effectively bypass safety filters while producing sensitive images, exposing safety vulnerabilities of T2I models. However, due to the LLM’s limited understanding […]
Best Practices for Biorisk Evaluations on Open-Weight Bio-Foundation Models
arXiv:2510.27629v4 Announce Type: replace-cross Abstract: Open-weight bio-foundation models present a dual-use dilemma. While holding great promise for accelerating scientific research and drug development, they could also enable bad actors to develop more deadly bioweapons. To mitigate the risk posed by these models, current approaches focus on filtering biohazardous data during pre-training. However, the effectiveness of […]
Planning with Sketch-Guided Verification for Physics-Aware Video Generation
arXiv:2511.17450v1 Announce Type: cross Abstract: Recent video generation approaches increasingly rely on planning intermediate control signals such as object trajectories to improve temporal coherence and motion fidelity. However, these methods mostly employ single-shot plans that are typically limited to simple motions, or iterative refinement which requires multiple calls to the video generator, incuring high computational […]
Artificial Intelligence Index Report 2025
arXiv:2504.07139v3 Announce Type: replace Abstract: Welcome to the eighth edition of the AI Index report. The 2025 Index is our most comprehensive to date and arrives at an important moment, as AI’s influence across society, the economy, and global governance continues to intensify. New in this year’s report are in-depth analyses of the evolving landscape […]
LLM Collaboration With Multi-Agent Reinforcement Learning
arXiv:2508.04652v4 Announce Type: replace Abstract: A large amount of work has been done in Multi-Agent Systems (MAS) for modeling and solving problems with multiple interacting agents. However, most LLMs are pretrained independently and not specifically optimized for coordination. Existing LLM fine-tuning frameworks rely on individual rewards, which require complex reward designs for each agent to […]
RTMol: Rethinking Molecule-text Alignment in a Round-trip View
arXiv:2511.12135v2 Announce Type: replace Abstract: Aligning molecular sequence representations (e.g., SMILES notations) with textual descriptions is critical for applications spanning drug discovery, materials design, and automated chemical literature analysis. Existing methodologies typically treat molecular captioning (molecule-to-text) and text-based molecular design (text-to-molecule) as separate tasks, relying on supervised fine-tuning or contrastive learning pipelines. These approaches face […]
Local equations for the generalized Lotka-Volterra model on sparse asymmetric graphs
arXiv:2511.17499v1 Announce Type: new Abstract: Real ecosystems are characterized by sparse and asymmetric interactions, posing a major challenge to theoretical analysis. We introduce a new method to study the generalized Lotka-Volterra model with stochastic dynamics on sparse graphs. By deriving local Fokker-Planck equations and employing a mean-field closure, we can efficiently compute stationary states for […]
Instance Configuration for Sustainable Job Shop Scheduling
arXiv:2409.18972v1 Announce Type: cross Abstract: The Job Shop Scheduling Problem (JSP) is a pivotal challenge in operations research and is essential for evaluating the effectiveness and performance of scheduling algorithms. Scheduling problems are a crucial domain in combinatorial optimization, where resources (machines) are allocated to job tasks to minimize the completion time (makespan) alongside other […]
Joint Design of Protein Surface and Structure Using a Diffusion Bridge Model
arXiv:2511.16675v1 Announce Type: cross Abstract: Protein-protein interactions (PPIs) are governed by surface complementarity and hydrophobic interactions at protein interfaces. However, designing diverse and physically realistic protein structure and surfaces that precisely complement target receptors remains a significant challenge in computational protein design. In this work, we introduce PepBridge, a novel framework for the joint design […]
Shona spaCy: A Morphological Analyzer for an Under-Resourced Bantu Language
arXiv:2511.16680v1 Announce Type: cross Abstract: Despite rapid advances in multilingual natural language processing (NLP), the Bantu language Shona remains under-served in terms of morphological analysis and language-aware tools. This paper presents Shona spaCy, an open-source, rule-based morphological pipeline for Shona built on the spaCy framework. The system combines a curated JSON lexicon with linguistically grounded […]