Latest papers
Writing Answer Set Programming (ASP) theories from scratch is a difficult and time-consuming task. We take a neurosymbolic approach to study whether a model can distill complete and correct theories, given a fixed agent harness with the…
Altermagnets constitute a novel class of collinear spin-compensated materials in which magnon branches are spin-split even in the non-relativistic limit. The latter is the result of a more complex symmetry operation (compared to…
Interpreting asteroid family albedo distributions as compositional signatures requires distinguishing intrinsic structure from measurement artifacts, rarely quantified. We analyze 102 families using NEOWISE data with AKARI cross-validation…
Artificial intelligence (AI) is rapidly evolving from a centralized computing capability into a pervasive infrastructure that interacts directly with the physical world. While recent perspectives highlight the roles of energy, chips,…
Large language models (LLMs) have demonstrated strong capabilities in structured query generation, making them a natural choice for Text-to-SPARQL, which translates natural language questions into executable SPARQL queries over knowledge…
Integrated sensing and communication(ISAC), as a rapidly advancing technique, introduces a fresh approach for achieving secure communication and intelligent sensing for future wireless networks. An ISAC framework empowered by simultaneously…
We extend a recently introduced Entropy-Optimal Manifold Clustering (EOMC) to allow for a joint simultaneous identification of subsets and subspaces of relevant features in nonstationary and nonlinear regression problems. It is shown that…
Chemical property prediction plays a critical role in accelerating scientific discovery in chemistry, materials science, and drug development. However, existing benchmarks often suffer from limited task diversity, fragmented datasets, and…
We establish strong existence and pathwise uniqueness for McKean-Vlasov stochastic differential equations with coefficients satisfying a distribution-dependent Lyapunov condition. Under a hybrid Perron-Nagumo condition that permits a…
Reinforcement learning with verifiable rewards (RLVR) improves the reasoning capabilities of large language models, but prompt groups with identical rollout rewards consume generation budget without effective learning signals. Pre-rollout…
Reinforcement learning with verifiable rewards (RLVR) is effective for training large language model agents. However, terminal rewards provide only coarse trajectory-level supervision, leaving successful behaviors, recurring mistakes, and…
Backdoor attacks on Spiking Neural Networks (SNNs) have primarily assumed dirty-label poisoning, in which triggered training samples are relabeled to an attacker-selected class. We study clean-label temporal poisoning, where a fixed…
Computer-use agents learn from what their actions change, so training one needs applications it can act on, break and reset. The applications that matter most are login-gated and stateful, so synthetic environments stand in for them. Recent…
In demanding professional environments and meeting review scenarios, lengthy text often imposes a high cognitive load. To facilitate efficient information communication, transforming verbose text into logically clear diagrams is essential.…
Commuters often encounter crowding in railway systems, particularly in queues where passenger density varies throughout the day. This introduces uncertainty in crowdedness, making it difficult for individuals to anticipate conditions and…
Let $F$ denote the Fano plane, the $3$-uniform hypergraph with $7$ vertices and $7$ edges. Frankl and F\"uredi, and independently Keevash and Sudakov, proved that the largest $F$-free subhypergraph of $K_n^{(3)}$ is bipartite. In this…
Recent studies in industrial recommendation systems have demonstrated that sequential recommendation models built upon self-attention can benefit from predictable scaling laws by increasing sequence length and model capacity. However,…
Long-context retrieval and agentic workloads repeatedly reuse the same documents under changing instructions, histories, and document orders. Prefix caching cannot exploit this reuse, while position-independent caching (PIC) remains…
Human cortical organoids provide an experimentally accessible model of early neural circuit formation, yet whether their activity reflects structured information processing rather than spontaneous synchronization is unclear. We developed a…
Achieving magnetically switchable chiral light emission is an important goal for 2D opto-spintronics. However, conventional strategies face a fundamental trade-off between dynamic tunability and polarization contrast. Nonlinear optics,…