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Event-SAMA: Language-Grounded Video Object Segmentation on Neuromorphic Event Streams
Event cameras offer microsecond temporal resolution, high dynamic range and no motion blur, but referring video object segmentation (RVOS) lacks event-stream datasets and models.From the Transformer to a Formal Semantics of Coordinated Transformations
We develop a formal semantics for a general class of coordinated systems of parameterized transformations, taking the Transformer as a paradigmatic starting point but abstracting from its particular…When the Top Answer Decides: Gender Bias in Decision Models
Decision models are language models built to route, classify and triage: they return option probabilities from one forward pass, and an application acts on the top answer.The Role of Self-Concept In Language Models
When a language model says "I," does it refer to its parameter weights, its currently running process, its stable preferences, its model lineage, or the goals it pursues?Grammar Control for Language Learning with Sequential Monte Carlo and Small Language Models
Second language learners benefit from exposure to level-appropriate grammar in interactive language use.Surprise Alone Learns Lies: Evidence-Gated Continual Learning for LLMs from Streaming Claims
Continual learning methods for large language models increasingly decide what to learn by surprise, keeping the inputs the model finds least predictable.KV Cache Quantization for Diffusion Language Models
KV cache quantization is well studied for autoregressive language models, where cached prefix states are exact under causal attention and quantization is mainly a cache reconstruction problem.Attention, Dynamic Wave and Hybrid Sequence Mixers in Language Models
Large Language Models (LLMs) rely on Multi-Head Attention (MHA) for sequence modeling, but scaling to long contexts is constrained by the quadratic cost of attention, motivating sub-quadratic…Tokenizer Tokens Tell Training Tales
Tokenizers are usually treated as fixed preprocessing tools, but they are trained on text and can retain traces of that text in their vocabularies.Prompts and probabilities in the linguistic assessment of language models: Evidence from semantic focus-sensitivity
As language models (LMs) have improved, an increasingly common means of evaluating their linguistic competence is through explicit prompting (e.g., "Which sentence is more acceptable?").Can LLMs Ignore What They Know? Measuring Knowledge Leakage in Persona-Based User Simulation
When persona-conditioned responses are read as respondent-level simulations, each response should reflect the described persona's knowledge, and the respondent written to know nothing must act as if…AI Cosmos: An Agentic Infra for Situated Learning
Large language models (LLMs) can improve task performance during learning, yet these gains do not necessarily reflect learners' ability to thereafter apply the knowledge and skills independently.Rethinking Pre-pretraining
We report that allocating compute to synthetic pre-pretraining (PPT) never outperforms pure natural-language training in our compute-matched experiments.One Vector or Many? Clustered Optimal-Transport Steering under Quantization
Activation steering changes what a language model generates by editing its hidden states at inference time.Upcycling Language Models for Multiple Specialized Domains
Effective multi-domain adaptation of large language models requires prioritizing relevant domain knowledge while minimizing interference from irrelevant domains.It Takes Two to Probe, Thousands to Retrieve: Putting Vision--Language Probes to the Retrieval Test
Vision--language models (VLMs) are tested for fine-grained understanding with image--text matching probes, a model must prefer the correct image or caption over handcrafted negative.Towards Full-Text Scholarly Argument Mining using Entity-Anchored Claim Extraction
Argument mining in full-text scholarly articles remains an important yet challenging task.EpiAgent: Epistemic Self-Play for LLM Agents
Epistemic game theory explains an agent's strategic behavior via the beliefs it holds about others and how these beliefs are updated as the interactions unfold.Mobilizing the Archive: Bitext Extraction at Scale from Archival Documents for Extremely Low-resource Languages
While mining parallel sentences from web pages has proven effective for low-resource machine translation, the majority of the world's languages have little to no web presence.ScienceJudge: Pattern Perturbation Augmentation for Sentence-Level Scientific Claim Verification
Sentence-level scientific claim verification determines whether each sentence in an AI-generated scientific paragraph is supported by a given multimodal evidence bundle.