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Valentine's Day dangers: Dating app killers lure love seekers in unsuspecting ways
Kurt "The Cyberguy" Knutsson explains how facial recognition technology can help you find your perfect match. From a poisonous date to finding love with a serial killer, these six chilling cases show how unsuspecting dating app users on the quest for romance led them into the clutches of danger. Dating apps – from Tinder to Grindr – are the modern way for people to connect with potential partners from the comfort of their own space. Brace yourself for stories that blur the line between love and terror. Here is Fox News Digital's list of some recent cases where love went wrong.
- North America > United States > New York (0.06)
- North America > United States > Pennsylvania (0.06)
- Oceania > New Zealand > North Island > Auckland Region > Auckland (0.05)
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- Law > Criminal Law (1.00)
- Law Enforcement & Public Safety > Crime Prevention & Enforcement (1.00)
- Information Technology (1.00)
Expect the Unexpected: FailSafe Long Context QA for Finance
Kamble, Kiran, Russak, Melisa, Mozolevskyi, Dmytro, Ali, Muayad, Russak, Mateusz, AlShikh, Waseem
We propose a new long-context financial benchmark, FailSafeQA, designed to test the robustness and context-awareness of LLMs against six variations in human-interface interactions in LLM-based query-answer systems within finance. We concentrate on two case studies: Query Failure and Context Failure. In the Query Failure scenario, we perturb the original query to vary in domain expertise, completeness, and linguistic accuracy. In the Context Failure case, we simulate the uploads of degraded, irrelevant, and empty documents. We employ the LLM-as-a-Judge methodology with Qwen2.5-72B-Instruct and use fine-grained rating criteria to define and calculate Robustness, Context Grounding, and Compliance scores for 24 off-the-shelf models. The results suggest that although some models excel at mitigating input perturbations, they must balance robust answering with the ability to refrain from hallucinating. Notably, Palmyra-Fin-128k-Instruct, recognized as the most compliant model, maintained strong baseline performance but encountered challenges in sustaining robust predictions in 17% of test cases. On the other hand, the most robust model, OpenAI o3-mini, fabricated information in 41% of tested cases. The results demonstrate that even high-performing models have significant room for improvement and highlight the role of FailSafeQA as a tool for developing LLMs optimized for dependability in financial applications. The dataset is available at: https://huggingface.co/datasets/Writer/FailSafeQA
- North America > United States > New York > New York County > New York City (0.04)
- North America > United States > California > San Bernardino County > Barstow (0.04)
- Asia > Thailand > Bangkok > Bangkok (0.04)
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- Information Technology (0.88)
- Law > Business Law (0.68)
- Banking & Finance > Trading (0.46)
- Government > Regional Government > North America Government > United States Government (0.46)
Stephen A. Smith 'loves' PGA Tour merger with LIV, calls it a 'smart business' move
Fox News Flash top sports headlines are here. Check out what's clicking on Foxnews.com. Tuesday's bombshell news that the PGA Tour, DP World Tour and LIV Golf would merge in order to "unify the game of golf, on a global basis" took almost everybody by surprise. The agreement ends "two years of disruption and distraction" between the PGA and the Saudi-backed invitational while creating a "transformational partnership" between the three entities. While many are unhappy with the agreement, one ESPN analyst is a big fan of the move.
- North America > United States > Oklahoma > Tulsa County > Broken Arrow (0.06)
- North America > United States > Florida > Saint Johns County > Ponte Vedra Beach (0.06)
- North America > United States > Arizona > Maricopa County > Phoenix (0.06)
- Asia > Middle East > Saudi Arabia (0.06)
Improving generation quality of pointer networks via guided attention
Chawla, Kushal, Krishna, Kundan, Srinivasan, Balaji Vasan
Pointer generator networks have been used successfully for abstractive summarization. Along with the capability to generate novel words, it also allows the model to copy from the input text to handle out-of-vocabulary words. In this paper, we point out two key shortcomings of the summaries generated with this framework via manual inspection, statistical analysis and human evaluation. The first shortcoming is the extractive nature of the generated summaries, since the network eventually learns to copy from the input article most of the times, affecting the abstractive nature of the generated summaries. The second shortcoming is the factual inaccuracies in the generated text despite grammatical correctness. Our analysis indicates that this arises due to incorrect attention transition between different parts of the article. We propose an initial attempt towards addressing both these shortcomings by externally appending traditional linguistic information parsed from the input text, thereby teaching networks on the structure of the underlying text. Results indicate feasibility and potential of such additional cues for improved generation.
- Europe > Spain > Galicia > Madrid (0.05)
- North America > United States > Washington (0.04)
- Asia > Japan (0.04)
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Lame duck, indeed
Co-chairs of The Problem Solvers Caucus Republican Rep. Tom Reed and Democrat Rep. Josh Gottheimer speak out on moving past gridlock in Washington. On the roster: Lame duck, indeed - H.W. Bush-era AG eyed as possible Sessions successor - GOP officials had early warning of voter fraud in N.C. - SupCo's double-jeopardy case holds Mueller probe implications - Will study for bacon LAME DUCK, INDEED In the universe of Washington dud stories, "government shutdown looming" is right up there with "fireworks expected at hearing" and "leadership challenge brewing." The witness shrugs off lame speechifying disguised as tough questioning, the insurgency peters out over the question "who else" and in all but five cases since 1990 the government makes it past the fiscal cliff by plopping out some temporary spending measure. And yet… Congress today passed a two-week extension of current spending while the lame-duck House and Senate bicker over how to proceed. At issue are seven stalled annual appropriations bills that fund nine cabinet agencies.
- Asia > Russia (0.67)
- North America > United States > North Carolina > Bladen County (0.15)
- North America > United States > Ohio (0.06)
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