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Computation & Language / NLP
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Newest papers, page 56
SPOOK: Sparse Pixel Optimization for Off-Manifold Knowledge in Vision Encoders
Modern vision encoders are widely used as semantic representations, but the relationship between embedding similarity and human-visible semantics can become unclear far from the natural-image…Communicating with the Entire Population: Machine Translation of Emergency Alerts and Warnings
It is essential that we communicate with the entirety of an affected population during a crisis, including those who do not speak a region's dominant language(s).Interpretable sparse fine-tuning with TopKLoRA enables faithful circuit discovery
Fine-tuning on datasets of unknown origin can create a backdoor in the trained model when the data includes poisoned examples.J-Comm: Jacobian-Guided Latent Communication between LLM Agents
Latent communication requires both an effective continuous reasoning process and an interface through which an external model can leverage its intermediate computation.Do "True" and "False" Add Up to One? Complement Consistency in LLM-Agent Opinion Simulations
In LLM-agent opinion simulations, each agent reports the probability that a claim is true after seeing its own previous probability and the probabilities reported by its neighbors, and that number…Adaptive Frequency Threshold Byte Pair Encoding for Mixed Natural Language and Structured Symbolic Corpora
Modern language models rely on subwording tokenization to define the discrete units of input processing, typically using methods like Byte Pair Encoding (BPE) that treat whitespace as a fixed…Yalda-Embedding: Open Development of a Competitive Persian Retrieval Model
Despite advances in multilingual text representations, effective dense retrieval for Persian remains constrained by the limited availability of language-specific training resources and compact…Measure Before You Train: Typed Decision Models vs. a Classical Baseline vs. a Generative LLM for Routing a Personal Multilingual Inbox
Personal email agents decide, for every message, what it is, whether it is urgent, whether to draft a reply, create a task, or ignore it.The Language of Instruction: Genre and Generative AI
This article argues that instruction-fine-tuned language models should be understood as implementing a genre, what is proposed as the instructional-conversational genre.Speculative Forking: Turning Idle Wait into Parallel Exploration for Repository Environment Setup
Before developers can use a software project, they must first get it to run.LLMs Can Tackle High Energy Theoretical Physics, yet Gaps Remain: Part I, Quantum Field Theory
Beyond math and code, Large language models (LLMs) are beginning to tackle problems that have traditionally required substantial training for theoretical physicists, but it remains unclear how far…Propensities Please: Exposing Alignment-Faking LLMs using Synthetic Document Finetuning
Alignment evaluations aim to assess whether large language models would engage in dangerous misaligned behaviour.Position, Role or Label? A Controlled Study of Instruction Conflicts in LLM Agents
LLM agents take instructions from the operator, repository configuration, user, tool results and saved memory, which often conflict.Of Chains and Gains: What Reinforcement Learning changes on Reasoning-based Image Quality Assessment
Reinforcement Learning with Verifiable Rewards (RLVR) has improved the performance of large Vision-Language Models (VLMs) on image quality assessment (IQA).Each Insufficient in Its Own Way: Calibrating Language Models Across Varying Evidence States
How can a language model know whether it has enough evidence to answer?Hey, guess what: CUES lead to inferences about typicality
Throughout life, we accumulate knowledge of how typical certain events are.Two Uncertainties Are Not One: Disagreement versus Decision-Risk in Cheap Structured Content Moderation
Content moderation compresses a graded, contested human judgment into a binary act (leave up / take down) over billions of items, at a scale where running a frontier LLM on every post is uneconomical.FlexA-Mem: Budget-Adaptive Agentic Memory for LLM Agents
Large language model (LLM) agents work in scenarios with very different memory needs.Multi-Agent Retrieval-Augmented Causality Assessment (MARCA) of Individual Case Safety Reports in Pharmacovigilance
Increasing volumes of individual case safety reports (ICSRs) challenge expert-led causality assessment in pharmacovigilance.The Emergence and Sparsification of a Syntactic Circuit
To understand the emergence of grammatical behavior in language models, we track circuits for subject-verb number agreement in pythia-1b and ten seeds of pythia-410m across training.