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arXiv:2511.02844v2 Announce Type: replace Abstract: Quantum computing education requires students to move beyond classical programming intuitions related to state, determinism, and debugging, and to develop...
arXiv:2511.03369v3 Announce Type: replace Abstract: Safety-aligned large language models (LLMs) are becoming increasingly widespread, especially in sensitive applications where fairness is essential and biased outputs...
arXiv:2511.04084v2 Announce Type: replace Abstract: Medical image segmentation is critical for accurate diagnostics and treatment planning, but remains challenging due to complex anatomical structures and...
arXiv:2511.04235v3 Announce Type: replace Abstract: Constructing a consistent shared spatial memory is a critical challenge in multi-agent systems, where partial observability and limited bandwidth often...
arXiv:2511.04427v3 Announce Type: replace Abstract: Large language models (LLMs) have demonstrated the promise to revolutionize the field of software engineering. Among other things, LLM agents...
arXiv:2511.04659v4 Announce Type: replace Abstract: Reliable nowcasting of extreme precipitation remains difficult because convective systems are strongly nonlinear, multiscale, and nonstationary in 3D. Radar is...
arXiv:2511.04768v2 Announce Type: replace Abstract: As deep learning models scale, sparse computation and specialized dataflow hardware have emerged as powerful solutions to address efficiency. We...
arXiv:2511.05293v2 Announce Type: replace Abstract: Electroencephalogram (EEG)-based emotion recognition is vital for affective computing but faces challenges in feature utilization and cross-domain generalization. This work...
arXiv:2511.05843v2 Announce Type: replace Abstract: Multi-Byzantine Fault Tolerant (Multi-BFT) consensus, which runs multiple BFT instances in parallel, has recently emerged as a promising approach to...
arXiv:2511.05903v2 Announce Type: replace Abstract: User simulation is important for developing and evaluating human-centered AI, yet current student simulation in educational applications has significant limitations....
arXiv:2511.08091v2 Announce Type: replace Abstract: Pearl's Causal Hierarchy (PCH) is a central framework for reasoning about probabilistic, interventional, and counterfactual statements, yet the satisfiability problem...
arXiv:2511.08150v5 Announce Type: replace Abstract: Generative retrieval (GR) reframes document retrieval as an end-to-end task of generating sequential document identifiers (DocIDs). Existing GR methods predominantly...
arXiv:2511.09957v2 Announce Type: replace Abstract: The increasingly sophisticated environment in which attackers operate makes software security an even greater challenge in open-source projects, where malicious...
arXiv:2511.10683v2 Announce Type: replace Abstract: Real-world datasets typically exhibit long-tailed (LT) distributions, where a few head classes dominate and many tail classes are severely underrepresented....
arXiv:2511.11057v2 Announce Type: replace Abstract: Nishimoto and Tabei [CPM, 2021] proposed r-enum, an algorithm to enumerate various characteristic substrings, including maximal repeats, in a string...
arXiv:2511.11233v2 Announce Type: replace Abstract: Table reasoning with large language models (LLMs) plays a critical role in building intelligent systems capable of understanding and analyzing...
arXiv:2511.11293v2 Announce Type: replace Abstract: Current cancer screening guidelines cover only a few cancer types and rely on narrowly defined criteria such as age or...
arXiv:2511.12487v2 Announce Type: replace Abstract: Large Language Models remain vulnerable to adversarial prompts that elicit toxic content even after safety alignment. We present ToxSearch, a...
arXiv:2511.12518v2 Announce Type: replace Abstract: In large-scale industrial recommendation systems, retrieval must produce high-quality candidates from massive corpora under strict latency. Recently, Generative Retrieval (GR)...
arXiv:2511.13095v2 Announce Type: replace Abstract: We introduce BeDiscovER (Benchmark of Discourse Understanding in the Era of Reasoning Language Models), an up-to-date, comprehensive suite for evaluating...
arXiv:2511.14702v2 Announce Type: replace Abstract: Accurate segmentation of myocardial scar from late gadolinium enhanced (LGE) cardiac MRI is essential for evaluating tissue viability, yet remains...
arXiv:2511.15169v3 Announce Type: replace Abstract: Large Reasoning Models (LRMs) have significantly improved problem-solving through explicit Chain-of-Thought (CoT) reasoning. However, this capability creates a Safety-Helpfulness Paradox:...
arXiv:2511.15331v2 Announce Type: replace Abstract: Recent large language models (LLMs) show promise in design tasks, yet a fundamental misalignment persists: design thinking requires iterative intent...
arXiv:2511.16629v2 Announce Type: replace Abstract: Policy gradient methods, which have been extensively studied in the last decade, offer an effective and efficient framework for reinforcement...