Model releases, architecture work and prompting research on large language models — from frontier-lab announcements to the arXiv papers behind them.
arXiv:2608. 12627v1 Announce Type: cross Abstract: Long-horizon egocentric memory transforms continuous first-person video and audio into a searchable record of past experiences.
arXiv:2608. 12444v1 Announce Type: cross Abstract: An unconditional risk bound on automated decisions can be satisfied without automating anything, since a selector that never acts drives the bound to zero.
arXiv:2608. 13450v1 Announce Type: cross Abstract: Autonomous vehicles depend on large safety-critical software stacks, where weaknesses reachable from adversarial inputs may affect steering, braking, or other control decisions.
arXiv:2608. 13510v1 Announce Type: cross Abstract: Machine learning procedures are commonly evaluated in terms of predictive accuracy and computational efficiency.
arXiv:2605. 18383v2 Announce Type: replace Abstract: We present TabH2O, a foundation model for tabular data that performs classification and regression in a single forward pass via in-context learning.
arXiv:2608. 12751v1 Announce Type: cross Abstract: Logic synthesis transforms RTL designs into gate-level netlists, where PPA results are highly sensitive to the choice of optimization commands, making synthesis tuning both high-dimensional and expensive.
arXiv:2608. 13200v1 Announce Type: cross Abstract: Modern LLMs excel at reasoning and instruction following, enabling users to express complex and diverse information needs.
arXiv:2608. 12389v1 Announce Type: new Abstract: Cross-domain zero- or few-shot personalization aims to generate user-preferred responses in unseen conversational domains from only a handful of target-domain interactions.
arXiv:2608. 12522v1 Announce Type: new Abstract: LLM-based program evolution systems such as FunSearch and AlphaEvolve have shown strong ability to discover novel algorithms, but typically optimize each task in isolation, discarding search experience after completion.
arXiv:2608. 12645v1 Announce Type: new Abstract: LLM judges have become central infrastructure for model evaluations, online grading, and reward modeling.
arXiv:2608. 12851v1 Announce Type: new Abstract: Self-improving LLM agents convert successful trajectories into persistent cross-task state.
arXiv:2608. 13048v1 Announce Type: new Abstract: In this work, we introduce DMDIntel which uses dynamic mode decomposition (DMD) to make the predictions made by LLMs in a classification task interpretable.
arXiv:2608. 13069v1 Announce Type: new Abstract: Large language models (LLMs) are predominantly aligned to function as passive, sycophantic assistants.
arXiv:2608. 12333v1 Announce Type: cross Abstract: Vision-language models must associate visual entities with textual attributes.
arXiv:2608. 12348v1 Announce Type: cross Abstract: Streaming systems increasingly hand work to large language models (LLMs) -- writing pipelines, triaging alerts, reading logs -- and all of it assumes the model knows how event-time stream processing behaves.
arXiv:2608. 12719v1 Announce Type: cross Abstract: Routing each query to a cost-effective large language model (LLM) is critical for balancing quality and cost, yet most routers rely on a centralized task center to predict model performance, creating an information-risk mismatch and a scalability bottleneck as the model pool grows.
arXiv:2608. 12750v1 Announce Type: cross Abstract: LLM-based simulated clients are increasingly used to train novice counselors, evaluate LLM therapists, and generate synthetic data.
arXiv:2608. 12898v1 Announce Type: cross Abstract: Document parsing aims to transform unstructured documents into structured and machine-readable representations.
arXiv:2608. 12977v1 Announce Type: cross Abstract: The expanding operational capabilities of large language model (LLM) agents introduce sophisticated security threats.
arXiv:2608. 13160v1 Announce Type: cross Abstract: Multilingual retrieval-augmented generation (mRAG) equips large language models with access to globally distributed external knowledge for complex multilingual question answering.