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Computation & Language / NLP
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Newest papers, page 212
Late Attention Layers Alone Can Copy Entity Tokens, but Not Without Attending to Their Context
Large language models (LLMs) reliably perform entity copying, in which a model copies tokens referring to an entity, termed entity tokens, from the prompt into its output to answer a question.MS-GLA: Multi-Scale Gated Linear Attention for Addressing Representational Bottlenecks via Multi-Temporal Resolution
Gated Linear Attention (GLA) Transformers advance linear recurrent models through data-dependent gating, but face a core limitation: the fixed-capacity memory matrices across all heads operate at a…Tracing the Evolution of Oracle Bone Characters Across Three Millennia
Of the approximately 4,500 Oracle Bone Inscription (OBI) characters discovered from the Shang dynasty, only about 1,600 have been deciphered.QuanReview: Offline, Auditable Reconciliation of Human and LLM Span Annotations
Structured span annotations, such as quantities with their units, uncertainty modifiers, and event classes, are expensive to create and hard to keep trustworthy once language models enter the loop.Rethinking Personalized Generation: Test-Time Alignment via Factorized Ranking Models
Aligning large language models (LLMs) to diverse user preferences is fundamentally hindered by standard alignment paradigms that optimize for monolithic users.Reinforcing Agentic Creativity in Scientific Ideation with Night Science
Large language models (LLMs) excel at structured, verifiable tasks, but their low-entropy bias can produce homogeneous and predictable outputs, limiting their utility for open-ended scientific…Harness Learning Enables Generalizable Test-Time Adaptation
A language-model agent is jointly defined by its model and its harness, the executable program that organizes model calls, tool use, and information flow.Shockingly Simple Self-retrospection Improves Agentic Models Without RL
People learn not only by repeating successful actions, but also by recounting and explaining their experiences, revising their understanding to guide future behavior.Improving Test-Time Scaling with Adaptive Looped Transformers
Looped transformers have demonstrated promising parameter efficiency by reusing layers for latent computation.Towards Communication-Efficient Social Intelligence in Language Agents
Socially intelligent language agents must negotiate, coordinate, and resolve conflicting preferences while respecting the time and attention of both participants.How to Loop MoE: Flatten the Experts, Untie the Attention
Looped Transformers reuse one block of layers several times: by spending extra computation they push a model of fixed size further, and so use its parameters more fully; while sparse…Scaling Long-Form Story Generation via Narrative State Tracking
LLMs have demonstrated strong capabilities in creative writing.Retrieving Biblical Intertextual References in Karen Blixen's Seven Gothic Tales
Identifying intertextual references is central to literary scholarship, but computationally difficult when source material is transformed through paraphrase, allusion, historical language, and…Telescopic Language Models
One deployed language model must often serve many compute budgets, yet serving each budget still means a separate training or compression run per point.VehicleArena: A Realistic Urban Environment for Multi-Agent Driving
Real-world embodied agents often pursue independent objectives within a shared physical environment, where their actions can alter the conditions faced by others.Almost Human, Except When It Matters: VoxParity and the Decisions a Voice Should Change
A voice agent can handle almost every call on the words alone and still fail the few its sector's rules were written for.Question-Specific Knowledge Graphs for Efficient Visual Reasoning
Recent work in visual question answering has shown that vision-language models can exhibit strong reasoning capabilities by translating visual inputs into textual representations.Causal and Interpretable Structures in LLM Compositional Tasks
Large language models are able to solve tasks whose answers depend on not only individual input tokens, but also on relations among them.Mnemon: Raw Records, Fast Judgments, Slow Thoughts
Long-term memory lets an LLM assistant use a history it can no longer reread, and most memory systems build it by rewriting conversations into facts, graphs or typed memories at write time.A Polyphonic Conception of AI Understanding
When a doctor, a judge, or an engineer must decide whether to trust an AI model's output, they cannot avoid asking what the model understands.