- Self-adaptive Dataset Construction for Real-World Multimodal Safety Scenarios
Jingen Qu, Lijun Li, Bo Zhang, Yichen Yan, Jing Shao · Sep 4, 2025 · Citations: 0
Multimodal large language models (MLLMs) are rapidly evolving, presenting increasingly complex safety challenges.
- Mitigating Multimodal Hallucinations via Gradient-based Self-Reflection
Shan Wang, Maying Shen, Nadine Chang, Chuong Nguyen, Hongdong Li · Sep 3, 2025 · Citations: 0
Experiments across multiple benchmarks demonstrate that GACD effectively reduces hallucinations and improves the visual grounding of MLLM outputs.
- Implicit Actor Critic Coupling via a Supervised Learning Framework for RLVR
Jiaming Li, Longze Chen, Ze Gong, Yukun Chen, Lu Wang · Sep 2, 2025 · Citations: 0
Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.
- Do LLMs Adhere to Label Definitions? Examining Their Receptivity to External Label Definitions
Seyedali Mohammadi, Bhaskara Hanuma Vedula, Hemank Lamba, Edward Raff, Ponnurangam Kumaraguru · Sep 2, 2025 · Citations: 0
To address these questions, we conduct controlled experiments across multiple explanation benchmark datasets (general and domain-specific) and label definition conditions, including expert-curated, LLM-generated, perturbed, and swapped…
- BioBlue: Systematic runaway-optimiser-like LLM failure modes on biologically and economically aligned AI safety benchmarks for LLMs with simplified observation format
Roland Pihlakas, Sruthi Susan Kuriakose · Sep 2, 2025 · Citations: 0
Long Horizon
Many AI alignment discussions of "runaway optimisation" focus on RL agents: unbounded utility maximisers that over-optimise a proxy objective (e.g., "paperclip maximiser", specification gaming) at the expense of everything else.
- Error Notebook-Guided, Training-Free Part Retrieval in 3D CAD Assemblies via Vision-Language Models
Yunqing Liu, Nan Zhang, Zhiming Tan · Sep 1, 2025 · Citations: 0
Pairwise Preference Long Horizon
We additionally contribute a CAD dataset with human preference annotations.
- EO-1: An Open Unified Embodied Foundation Model for General Robot Control
Delin Qu, Haoming Song, Qizhi Chen, Zhaoqing Chen, Xianqiang Gao · Aug 28, 2025 · Citations: 0
Long Horizon
The human ability to seamlessly perform multimodal reasoning and physical interaction in the open world is a core goal for general purpose embodied intelligent systems.
- Dyslexify: A Mechanistic Defense Against Typographic Attacks in CLIP
Lorenz Hufe, Constantin Venhoff, Erblina Purelku, Maximilian Dreyer, Sebastian Lapuschkin · Aug 28, 2025 · Citations: 0
Red Team
These models serve as suitable drop-in replacements for a broad range of safety-critical applications, where the risks of text-based manipulation outweigh the utility of text recognition.
- NPG-Muse: Scaling Long Chain-of-Thought Reasoning with NP-Hard Graph Problems
Yuyao Wang, Bowen Liu, Jianheng Tang, Nuo Chen, Yuhan Li · Aug 28, 2025 · Citations: 0
However, developing these Long CoT behaviors relies heavily on post-training with high-quality datasets, which are typically costly and human-curated (e.g., mathematics and code), leaving scalable alternatives unexplored.
- Diffusion Language Models Know the Answer Before Decoding
Pengxiang Li, Yefan Zhou, Dilxat Muhtar, Lu Yin, Shilin Yan · Aug 27, 2025 · Citations: 0
Empirical evaluations of LLaDA-8B and Dream-7B across multiple tasks show that Prophet reduces the number of decoding steps by up to 3.4x while preserving high generation quality.
- Your AI Bosses Are Still Prejudiced: The Emergence of Stereotypes in LLM-Based Multi-Agent Systems
Jingyu Guo, Yingying Xu · Aug 27, 2025 · Citations: 0
Multi Agent
While stereotypes are well-documented in human social interactions, AI systems are often presumed to be less susceptible to such biases.
- Language and Experience: A Computational Model of Social Learning in Complex Tasks
Cédric Colas, Tracey Mills, Ben Prystawski, Michael Henry Tessler, Noah Goodman · Aug 26, 2025 · Citations: 0
The ability to combine linguistic guidance from others with direct experience is central to human development, enabling safe and rapid learning in new environments.
- Hybrid Deep Searcher: Scalable Parallel and Sequential Search Reasoning
Dayoon Ko, Jihyuk Kim, Haeju Park, Sohyeon Kim, Dahyun Lee · Aug 26, 2025 · Citations: 0
Long Horizon
Large reasoning models (LRMs) combined with retrieval-augmented generation (RAG) have enabled deep research agents capable of multi-step reasoning with external knowledge retrieval.
- Why Synthetic Isn't Real Yet: A Diagnostic Framework for Contact Center Dialogue Generation
Rishikesh Devanathan, Varun Nathan, Ayush Kumar · Aug 25, 2025 · Citations: 0
In this work, we benchmark multiple generation strategies guided by structured supervision on call attributes (Intent Summaries, Topic Flows, and Quality Assurance (QA) Forms) across multiple languages.
