Text understanding and language tasks
Been thinking about this and want to know if others have hit the same issue. The dominant approach for agent memory (Mem0, Zep, most RAG ...
![[2601.11016] Contextual Distributionally Robust Optimization with Causal and Continuous Structure: An Interpretable and Tractable Approach](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
Abstract page for arXiv paper 2601.11016: Contextual Distributionally Robust Optimization with Causal and Continuous Structure: An Interp...
Abstract page for arXiv paper 2511.22294: Structure is Supervision: Multiview Masked Autoencoders for Radiology
The paper introduces PinRec, a unified generative retrieval model for Pinterest's recommendation systems, enhancing performance across va...
This paper presents a novel algorithmic framework that integrates momentum terms with stochastic line search methods to optimize finite-s...
The MAPS algorithm offers a novel approach to generating model-agnostic, distribution-free prediction intervals in supervised learning, a...
This article explores the development of role-aware language models designed to enhance access control in organizational settings, focusi...
The paper presents AbstRaL, a method to enhance large language models' reasoning capabilities by reinforcing abstract thinking, particula...
The paper investigates 'Cross-lingual Collapse' in large language models (LLMs), revealing how reasoning capabilities can revert to a dom...
The paper introduces TextME, a framework that enables zero-shot cross-modal transfer using only text descriptions, addressing the limitat...
The paper presents BitHydra, a framework for executing bit-flip inference cost attacks on large language models (LLMs), demonstrating how...
This paper presents a novel distributionally robust learning framework for multi-source unsupervised domain adaptation, addressing challe...
This article surveys advancements in multi-turn interactions with large language models (LLMs), focusing on evaluation methods, challenge...
This article presents a novel approach to polyphonic music generation using structural inductive bias, focusing on Beethoven's piano sona...
The paper presents VQEL, a novel architecture that enhances self-play in emergent language games through agent-internal vector quantizati...
The paper presents FedCoLLM, a federated co-tuning framework that enhances the performance of both Large Language Models (LLMs) and Small...
The paper presents PoTable, a novel approach to table reasoning that integrates systematic thinking through a plan-then-execute mechanism...
The paper presents E2E-GRec, a novel end-to-end framework that integrates Graph Neural Networks (GNNs) with recommender systems, addressi...
This article presents RectiCast, a novel framework for improving precipitation nowcasting by addressing distribution shifts in deep learn...
This paper explores how autoregressive large language models (LLMs) assess thematic fit in event representation, achieving state-of-the-a...
The paper presents PASS, a novel algorithmic framework that utilizes visual prompts to enhance structural sparsity in neural networks, im...
This paper presents a novel approach to goal-conditioned reinforcement learning (GCRL) using multistep quasimetric learning, demonstratin...
Lean Finder is a semantic search engine designed for the Lean programming language and mathlib, improving theorem retrieval by understand...
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